Introduction

For one of my machine learning classes we had a project that consumed financial data. I have extended that project to use machine learning to see if an indicator, or predictor, can be found that identifies market tops that occur prior to recessions. Then I use the model to build a trading strategy and backtest it to see how it performs.

Get Economic and Financial Data

Acquiring the data consists of two steps. First the code pulls the data into zoo objects which are then collapsed into a single data frame (df.data). Features are extracted from these series and added to the df.data data frame.

Sample call to pull economic data

Data is pulled from several sources include FRED, yahoo, and Google. The code below shows an example that pulls in the consumer price index (CPI) from the FRED. I pull data using quantmod, Quandl, and some manual extractions stored in spreadsheets.

# Consumer Price Index for All Urban Consumers: All Items
if (bRefresh == TRUE) {
  getSymbols("CPIAUCSL", src = "FRED", auto.assign = TRUE)
}
## [1] "CPIAUCSL"
## Warning: ASDAX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: ^TNX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: CL=F contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: ^IRX contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: ^RLG contains missing values. Some functions will not work if objects
## contain missing values in the middle of the series. Consider using na.omit(),
## na.approx(), na.fill(), etc to remove or replace them.
## Warning: ^STOXX50E contains missing values. Some functions will not work if
## objects contain missing values in the middle of the series. Consider using
## na.omit(), na.approx(), na.fill(), etc to remove or replace them.

Load up the EIA data

## Warning in .getMonEIA(ID, key = key): NAs introduced by coercion

## Warning in .getMonEIA(ID, key = key): NAs introduced by coercion

Load rig count data

The Baker Hughes rig count numbers

USDA data

Loading in farm data

## Warning in read_fun(path = enc2native(normalizePath(path)), sheet_i = sheet, :
## Expecting numeric in E3 / R3C5: got a date
## New names:
## * `` -> ...1
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * ...
## Warning: NAs introduced by coercion

Loading in Silverblatt’s S&P 500 spreadsheet starting with the quarterly data.

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...5
## * `` -> ...6
## * `` -> ...7

Now load in the estimates

## New names:
## * `` -> ...2
## * `` -> ...3
## * `` -> ...4
## * `` -> ...5
## * `` -> ...6
## * ...

Covid 19 Data

Get the Covid-19 data from JHU

## Parsed with column specification:
## cols(
##   date = col_date(format = ""),
##   province = col_character(),
##   country = col_character(),
##   lat = col_double(),
##   long = col_double(),
##   type = col_character(),
##   cases = col_double(),
##   uid = col_double(),
##   iso2 = col_character(),
##   iso3 = col_character(),
##   code3 = col_double(),
##   combined_key = col_character(),
##   population = col_double(),
##   continent_name = col_character(),
##   continent_code = col_logical()
## )
## Warning: 434898 parsing failures.
##  row            col           expected actual                                                                                   file
## 1307 continent_code 1/0/T/F/TRUE/FALSE     AS 'https://raw.githubusercontent.com/RamiKrispin/coronavirus/master/csv/coronavirus.csv'
## 1308 continent_code 1/0/T/F/TRUE/FALSE     AS 'https://raw.githubusercontent.com/RamiKrispin/coronavirus/master/csv/coronavirus.csv'
## 1309 continent_code 1/0/T/F/TRUE/FALSE     AS 'https://raw.githubusercontent.com/RamiKrispin/coronavirus/master/csv/coronavirus.csv'
## 1310 continent_code 1/0/T/F/TRUE/FALSE     AS 'https://raw.githubusercontent.com/RamiKrispin/coronavirus/master/csv/coronavirus.csv'
## 1311 continent_code 1/0/T/F/TRUE/FALSE     AS 'https://raw.githubusercontent.com/RamiKrispin/coronavirus/master/csv/coronavirus.csv'
## .... .............. .................. ...... ......................................................................................
## See problems(...) for more details.
## No updates are available
## `summarise()` ungrouping output (override with `.groups` argument)
## `summarise()` regrouping output by 'country' (override with `.groups` argument)

## Warning: The `i` argument of ``[.tbl_df`()` must lie in [0, rows] if positive, as of tibble 3.0.0.
## Use `NA` as row index to obtain a row full of `NA` values.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.
## Warning: Removed 2 row(s) containing missing values (geom_path).

Feature Extraction

With the raw data downloaded, some of the interesting features can be extracted. The first step is reconcile the time intervals. Some of the data is released monthly and some daily. I chose to interpolate all data to a daily interval. The first section of code adds the daily rows to the dataframe.

The code performs interpolation for continuous data or carries it forward for binary data like the recession indicators.

source("calcInterpolate.r")
df.data <- calcInterpolate(df.data, df.symbols)
## Warning in merge.xts(xtsData, get(df.symbols$string.symbol[idx])): NAs
## introduced by coercion

Truncate data

Create aggregate series

Some analysis requires that two or more series be combined. For example, normallizing debt by GDP to get a sense of the proportion of debt to the total economy helps understand the debt cycle.

Year over year, smoothed derivative, and log trends tend to smooth out seasonal variation. It gets used so often that I do this for every series downloaded.

source("calcFeatures.r")
lst.df <- calcFeatures(df.data, df.symbols)
## [1] "USREC has zero or negative values. Log series will be zero."
## [1] "GSFTX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMIX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMCX.Volume has zero or negative values. Log series will be zero."
## [1] "LFMAX.Volume has zero or negative values. Log series will be zero."
## [1] "LCSIX.Volume has zero or negative values. Log series will be zero."
## [1] "VBIRX.Volume has zero or negative values. Log series will be zero."
## [1] "VFSUX.Volume has zero or negative values. Log series will be zero."
## [1] "LTUIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTPX.Volume has zero or negative values. Log series will be zero."
## [1] "NERYX.Volume has zero or negative values. Log series will be zero."
## [1] "STIGX.Volume has zero or negative values. Log series will be zero."
## [1] "HLGAX.Volume has zero or negative values. Log series will be zero."
## [1] "FTRGX.Volume has zero or negative values. Log series will be zero."
## [1] "THIIX.Volume has zero or negative values. Log series will be zero."
## [1] "PTTRX.Volume has zero or negative values. Log series will be zero."
## [1] "BFIGX.Volume has zero or negative values. Log series will be zero."
## [1] "EIFAX.Volume has zero or negative values. Log series will be zero."
## [1] "ASDAX.Volume has zero or negative values. Log series will be zero."
## [1] "TRBUX.Volume has zero or negative values. Log series will be zero."
## [1] "PRWCX.Volume has zero or negative values. Log series will be zero."
## [1] "ADOZX.Volume has zero or negative values. Log series will be zero."
## [1] "MERFX.Volume has zero or negative values. Log series will be zero."
## [1] "CMNIX.Volume has zero or negative values. Log series will be zero."
## [1] "CIHEX.Volume has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB has zero or negative values. Log series will be zero."
## [1] "TNX.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Open has zero or negative values. Log series will be zero."
## [1] "CLF.Low has zero or negative values. Log series will be zero."
## [1] "CLF.Close has zero or negative values. Log series will be zero."
## [1] "CLF.Volume has zero or negative values. Log series will be zero."
## [1] "CLF.Adjusted has zero or negative values. Log series will be zero."
## [1] "DTB3 has zero or negative values. Log series will be zero."
## [1] "IRX.Open has zero or negative values. Log series will be zero."
## [1] "IRX.High has zero or negative values. Log series will be zero."
## [1] "IRX.Low has zero or negative values. Log series will be zero."
## [1] "IRX.Close has zero or negative values. Log series will be zero."
## [1] "IRX.Volume has zero or negative values. Log series will be zero."
## [1] "IRX.Adjusted has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO has zero or negative values. Log series will be zero."
## [1] "RLG.Volume has zero or negative values. Log series will be zero."
## [1] "STOXX50E.Volume has zero or negative values. Log series will be zero."
## [1] "GDPNOW has zero or negative values. Log series will be zero."
## [1] "W790RC1Q027SBEA has zero or negative values. Log series will be zero."
## [1] "VXX.Volume has zero or negative values. Log series will be zero."
## [1] "FYFSD has zero or negative values. Log series will be zero."
## [1] "FYFSGDA188S has zero or negative values. Log series will be zero."
## [1] "SOFR25 has zero or negative values. Log series will be zero."
## [1] "SOFR1 has zero or negative values. Log series will be zero."
## [1] "RPONTSYD has zero or negative values. Log series will be zero."
## [1] "BOPGTB has zero or negative values. Log series will be zero."
## [1] "EES.Volume has zero or negative values. Log series will be zero."
## [1] "VGSTX.Volume has zero or negative values. Log series will be zero."
## [1] "VFINX.Volume has zero or negative values. Log series will be zero."
## [1] "TMFGX.Volume has zero or negative values. Log series will be zero."
## [1] "HAINX.Volume has zero or negative values. Log series will be zero."
## [1] "IVOO.Volume has zero or negative values. Log series will be zero."
## [1] "VO.Volume has zero or negative values. Log series will be zero."
## [1] "CZA.Volume has zero or negative values. Log series will be zero."
## [1] "SLY.Volume has zero or negative values. Log series will be zero."
## [1] "HYMB.Volume has zero or negative values. Log series will be zero."
## [1] "GOLD.Open has zero or negative values. Log series will be zero."
## [1] "GOLD.Volume has zero or negative values. Log series will be zero."
## [1] "BKR.Open has zero or negative values. Log series will be zero."
## [1] "BKR.Volume has zero or negative values. Log series will be zero."
## [1] "HAL.Open has zero or negative values. Log series will be zero."
## [1] "HAL.Volume has zero or negative values. Log series will be zero."
## [1] "IP.Open has zero or negative values. Log series will be zero."
## [1] "T.Open has zero or negative values. Log series will be zero."
## [1] "OPEARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "AREARNINGSPERSHARE has zero or negative values. Log series will be zero."
## [1] "OCCEquityVolume has zero or negative values. Log series will be zero."
## [1] "OCCNonEquityVolume has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA has zero or negative values. Log series will be zero."
## [1] "BUSLOANS.minus.BUSLOANSNSA.by.GDP has zero or negative values. Log series will be zero."
## [1] "EXPCH.minus.IMPCH has zero or negative values. Log series will be zero."
## [1] "EXPMX.minus.IMPMX has zero or negative values. Log series will be zero."
## [1] "SRPSABSNNCB.by.GDP has zero or negative values. Log series will be zero."
## [1] "DGS30TO10 has zero or negative values. Log series will be zero."
## [1] "DGS10TO1 has zero or negative values. Log series will be zero."
## [1] "DGS10TO2 has zero or negative values. Log series will be zero."
## [1] "DGS10TOTB3MS has zero or negative values. Log series will be zero."
## [1] "DGS10TODTB3 has zero or negative values. Log series will be zero."
## [1] "DCOILWTICO.by.PPIACO has zero or negative values. Log series will be zero."
## [1] "GSPC.DailySwing has zero or negative values. Log series will be zero."
df.data <- lst.df[[1]]
df.symbols <- lst.df[[2]]

Recession calculations

Summary calculations

These values are used below

Conclusion

In this worksheet a model predicting the onset of recession was built. From the model a trading rule was derived to allow backtesting. The model performed well and the trading rule backtesting showed that applying this in the post-WWII period would have resulted in an increase in returns. That is not too bad, but there are a few changes that would likely improve the model:

Market Conditions

#The model is predicting a `r paste(sprintf("%3.0f", tail(df.data$recession.initiation.smooth.avg,1)[[1]]*100), "%", sep="")` chance of recession in the next 12 months. :

#- P/E ratio of `r sprintf("%3.2f", tail(df.data$MULTPLSP500PERATIOMONTH,1))` compares to a historical mean value over the last decade of `r sprintf("%3.2f", df.data$MULTPLSP500PERATIOMONTH_Mean[1])`. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

As of Feb 2020 we have entered a recession as defined by the NBER yet the market continues to rise.

P/E ratio of 29.06 compares to a historical mean value over the last decade of 18.57. Since 2008 recession P/E has only fallen below historical norm a few times. The current value is high, but well off the peaks. If earnings are +2-4% year-over-year then it is not unrealistic.

  • S&P 500 Volume, last updated on 2021-11-04, is negative over the last year and positive over the last month.

Unemployment

  • Headline unemployment (U-3) stands at 4.80% (last updated on 2021-09-01) which is near the 1-year average of 5.72% and rising with respect to the low in the last twelve months of 4.80%. Unlikely the rate will drop again.

  • Payrolls (BLS data, NSA) year-over-year stands at 2.51% which is above the 1-year average of 1.61% and falling with respect to the peak, in the last twelve months, of 10.86%.

  • Jobless claims (ICSA data) year-over-year stands at -63.84% (last updated on 2021-10-30) which is in-line with the 1-year average of 50.50% and below the peak, in the last twelve months, of 337.62%.
## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).
## Warning: Removed 1 rows containing missing values (geom_text).
## Warning: Removed 1 rows containing missing values (geom_hline).

Personal Income

  • Real personal income year over year growth stands at 0.72% (last updated on 2021-09-01). This is below the recent peak of 8.08%.

Yield Curve and Bond Market

  • The 10-year to 3-month yield stands at 1.55% (last updated on 2021-11-03). This is above the recent low of 0.69%. The trend is positive over the last year and flat over the last month.

  • Auto sales flat?

Auxillary Series

I explored additional data series. The sections below have those data series along with comments.

Recent Highs

Print out the new 180 day high values

df.symbolsTrue <-
  df.symbols[df.symbols$'Max180' == TRUE, c("string.symbol", "string.description")]
df.symbolsTrue <-
  df.symbolsTrue[!(is.na(df.symbolsTrue$string.symbol)), ]
df.symbolsTrue <-
  df.symbolsTrue[!(df.symbolsTrue$string.symbol == 'USREC'), ]
#print(head(df.symbolsTrue,20))

kable(df.symbolsTrue, caption = "6-Month High") %>%
  kable_styling(bootstrap_options = c("striped", "hover"))  
6-Month High
string.symbol string.description
1 CPIAUCSL Consumer Price Index for All Urban Consumers: All Items
4 PCEPI Personal Consumption Expenditures: Chain-type Price Index
7 NPPTTL Total Nonfarm Private Payroll Employment (ADP)
9 PAYNSA All Employees: Total Nonfarm Payrolls (NSA)
10 TABSHNO Households and nonprofit organizations; total assets, Level
11 HNONWPDPI Household Net Worth, percent Dispsable Income
14 RSALES Real Retail Sales (DISCONTINUED)
15 W875RX1 Real personal income excluding current transfer receipts
49 IMPCH U.S. Imports of Goods by Customs Basis from China (Monthly, NSA)
53 HSN1FNSA New One Family Houses Sold: United States (Monthly, NSA)
54 HNFSUSNSA New One Family Houses for Sale in the United States (Monthly, NSA)
58 REALLNNSA Real Estate Loans, All Commercial Banks (Monthly, NSA)
59 REALLN Real Estate Loans, All Commercial Banks (Monthly, SA)
61 RELACBW027SBOG Real Estate Loans, All Commercial Banks (Weekly, SA)
62 RREACBM027NBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
63 RREACBM027SBOG Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
67 CONSUMERNSA Consumer Loans, All Commercial Banks
69 DPSACBW027SBOG Deposits, All Commercial Banks
70 DRCLACBS Delinquency Rate on Consumer Loans, All Commercial Banks, SA
72 SRPSABSNNCB Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
73 ASTLL All sectors; total loans; liability, Level (NSA)
74 FBDILNECA Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
75 ASOLAL All sectors; other loans and advances; liability, Level (NSA)
76 ASTMA All sectors; total mortgages; asset, Level (NSA)
77 ASHMA All sectors; home mortgages; asset, Level (NSA)
78 ASMRMA All sectors; multifamily residential mortgages; asset, Level (NSA)
79 ASCMA All sectors; commercial mortgages; asset, Level (NSA)
80 ASFMA All sectors; farm mortgages; asset, Level (NSA)
81 CCLBSHNO Households and nonprofit organizations; consumer credit; liability, Level (NSA)
82 FBDSILQ027S Domestic financial sectors debt securities; liability, Level (NSA)
83 FBLL Domestic financial sectors loans; liability, Level (NSA)
84 NCBDBIQ027S Nonfinancial corporate business; debt securities; liability, Level
89 DGS1 1-Year Treasury Constant Maturity Rate
91 TB3MS 3-Month Treasury Bill: Secondary Market Rate (Monthly)
96 NEWORDER Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
104 GDP Gross Domestic Product
106 FDEFX Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
107 GDPNOW Fed Atlanta GDPNow
108 GDPC1 Real Gross Domestic Product
109 GDPDEF Gross Domestic Product: Implicit Price Deflator
113 GPDI Gross Private Domestic Investment
114 W790RC1Q027SBEA Net domestic investment: Private: Domestic busines
115 MZMV Velocity of MZM Money Stock
116 M1 M1 Money Stock
117 M2 M2 Money Stock
121 GS5 5-Year Treasury Constant Maturity Rate
126 GFDEBTN Federal Debt: Total Public Debt
128 MSPUS Median Sales Price of Houses Sold for the United States
131 CSUSHPINSA S&P/Case-Shiller U.S. National Home Price Index (NSA)
132 GFDEGDQ188S Federal Debt: Total Public Debt as Percent of Gross Domestic Product
133 FYFSD Federal Surplus or Deficit
134 FYFSGDA188S Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
139 WALCL All Federal Reserve Banks: Total Assets
140 OUTMS Manufacturing Sector: Real Output
141 MANEMP All Employees: Manufacturing
142 PRS30006163 Manufacturing Sector: Real Output Per Person
145 SOFR Secured Overnight Financing Rate
147 SOFR99 Secured Overnight Financing Rate: 99th Percentile
155 OBFR1 Overnight Bank Funding Rate: 1st Percentile
157 IOER Interest Rate on Excess Reserves
159 EXCSRESNW Excess Reserves of Depository Institutions
160 ECBASSETS Central Bank Assets for Euro Area (11-19 Countries)
161 EUNNGDP Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
164 CURRENCY Currency Component of M1 (Seasonally Adjusted)
165 WCURRNS Currency Component of M1
166 BOGMBASE Monetary Base; Total
167 PRS88003193 Nonfinancial Corporations Sector: Unit Profits
168 PPIACO Producer Price Index for All Commodities
169 PCUOMFGOMFG Producer Price Index by Industry: Total Manufacturing Industries
170 POPTHM Population (U.S.)
171 POPTHM Population (U.S.)
176 RSAFS Advance Retail Sales: Retail and Food Services
180 A065RC1A027NBEA Personal income (NSA)
182 PCE Personal Consumption Expenditures (SA)
183 A053RC1Q027SBEA National income: Corporate profits before tax (without IVA and CCAdj)
184 CPROFIT Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
219 MULTPLSP500SALESQUARTER S&P 500 TTM Sales (Not Inflation Adjusted)
221 MULTPLSP500DIVMONTH S&P 500 Dividend by Month (Inflation Adjusted)
223 WWDIWLDISAIRGOODMTK1 Air transport, freight
226 PETA143B00001M U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
228 TOTALOGNRPUSM Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
229 TOTALPANRPUSM Crude Oil Rotary Rigs in Operation, Monthly
231 BKRTotal Total Rig Count
232 BKRGas Gas Rig Count
233 BKROil Oil Rig Count
234 FARMINCOME Net Farm Income
235 OPEARNINGSPERSHARE Operating Earnings per Share
236 AREARNINGSPERSHARE As-Reported Earnings per Share
237 CASHDIVIDENDSPERSHR Cash Dividends per Share
238 SALESPERSHR Sales per Share
239 BOOKVALPERSHR Book value per Share
240 CAPEXPERSHR Cap ex per Share
241 PRICE Price
242 OPEARNINGSTTM TTM Operating Earnings
243 AREARNINGSTTM TTM Reported Earnings
246 OCCEquityVolume Equity Options Volume
247 OCCNonEquityVolume Non-Equity Options Volume
249 BUSLOANS.minus.BUSLOANSNSA Business Loans (Montlhy) SA - NSA
250 BUSLOANS.minus.BUSLOANSNSA.by.GDP Business Loans (Montlhy) SA - NSA divided by GDP
264 CONSUMERNSA.by.GDP Consumer Loans Not Seasonally Adjusted divided by GDP
265 RREACBM027NBOG.by.GDP Residental Real Estate Loans (Monthly, NSA) divided by GDP
274 CONSUMERNSA.INTEREST Consumer Loans (Not Seasonally Adjusted) Interest Burdens
275 CONSUMERNSA.INTEREST.by.GDP Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
276 TOTLNNSA Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
289 ASFMA.by.ASTLL All sectors; total loans Divided by farm mortgages
293 BOGMBASE.by.GDP BOGMBASE Divided by GDP
294 WALCL.by.GDP All Federal Reserve Banks: Total Assets Divided by GDP
295 ECBASSETS.by.EUNNGDP Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
304 NPPTTLBYPOPTHM ADP Private Employment / Population
321 GSPC.Open.by.GDPDEF S&P 500 (^GSPC) Open divided by GDP deflator
322 GSPC.Close.by.GDPDEF S&P 500 (^GSPC) Close divided by GDP deflator
325 MSPUS.times.HNFSUSNSA New privately owned 1-family units for sale times median price
332 CPIAUCSL_Log Log of Consumer Price Index for All Urban Consumers: All Items
333 CPIAUCSL_mva200 Consumer Price Index for All Urban Consumers: All Items 200 Day MA
334 CPIAUCSL_mva050 Consumer Price Index for All Urban Consumers: All Items 50 Day MA
335 USREC_YoY NBER based Recession Indicators Year over Year
336 USREC_YoY4 NBER based Recession Indicators 4 Year over 4 Year
337 USREC_YoY5 NBER based Recession Indicators 5 Year over 5 Year
338 USREC_Smooth Savitsky-Golay Smoothed (p=3, n=365) NBER based Recession Indicators
339 USREC_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) NBER based Recession Indicators
340 USREC_SmoothDer Derivative of Smoothed NBER based Recession Indicators
341 USREC_Log Log of NBER based Recession Indicators
342 USREC_mva200 NBER based Recession Indicators 200 Day MA
343 USREC_mva050 NBER based Recession Indicators 50 Day MA
344 UNRATE_YoY Civilian Unemployment Rate U-3 Year over Year
359 PCEPI_Log Log of Personal Consumption Expenditures: Chain-type Price Index
360 PCEPI_mva200 Personal Consumption Expenditures: Chain-type Price Index 200 Day MA
361 PCEPI_mva050 Personal Consumption Expenditures: Chain-type Price Index 50 Day MA
362 CCSA_YoY Continued Claims (Insured Unemployment) Year over Year
371 CCNSA_YoY Continued Claims (Insured Unemployment, NSA) Year over Year
386 NPPTTL_Log Log of Total Nonfarm Private Payroll Employment (ADP)
387 NPPTTL_mva200 Total Nonfarm Private Payroll Employment (ADP) 200 Day MA
388 NPPTTL_mva050 Total Nonfarm Private Payroll Employment (ADP) 50 Day MA
389 U6RATE_YoY Total unemployed + margin + part-time U-6 Year over Year
403 PAYNSA_SmoothDer Derivative of Smoothed All Employees: Total Nonfarm Payrolls (NSA)
404 PAYNSA_Log Log of All Employees: Total Nonfarm Payrolls (NSA)
405 PAYNSA_mva200 All Employees: Total Nonfarm Payrolls (NSA) 200 Day MA
406 PAYNSA_mva050 All Employees: Total Nonfarm Payrolls (NSA) 50 Day MA
413 TABSHNO_Log Log of Households and nonprofit organizations; total assets, Level
414 TABSHNO_mva200 Households and nonprofit organizations; total assets, Level 200 Day MA
415 TABSHNO_mva050 Households and nonprofit organizations; total assets, Level 50 Day MA
422 HNONWPDPI_Log Log of Household Net Worth, percent Dispsable Income
423 HNONWPDPI_mva200 Household Net Worth, percent Dispsable Income 200 Day MA
424 HNONWPDPI_mva050 Household Net Worth, percent Dispsable Income 50 Day MA
432 INDPRO_mva200 Industrial Production Index 200 Day MA
443 RSALES_YoY Real Retail Sales (DISCONTINUED) Year over Year
444 RSALES_YoY4 Real Retail Sales (DISCONTINUED) 4 Year over 4 Year
445 RSALES_YoY5 Real Retail Sales (DISCONTINUED) 5 Year over 5 Year
449 RSALES_Log Log of Real Retail Sales (DISCONTINUED)
450 RSALES_mva200 Real Retail Sales (DISCONTINUED) 200 Day MA
451 RSALES_mva050 Real Retail Sales (DISCONTINUED) 50 Day MA
457 W875RX1_SmoothDer Derivative of Smoothed Real personal income excluding current transfer receipts
458 W875RX1_Log Log of Real personal income excluding current transfer receipts
459 W875RX1_mva200 Real personal income excluding current transfer receipts 200 Day MA
460 W875RX1_mva050 Real personal income excluding current transfer receipts 50 Day MA
481 NOBL.Open_YoY5 5 Year over 5 Year
483 NOBL.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
485 NOBL.Open_Log Log of
486 NOBL.Open_mva200 200 Day MA
492 NOBL.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
494 NOBL.High_Log Log of
495 NOBL.High_mva200 200 Day MA
499 NOBL.Low_YoY5 5 Year over 5 Year
501 NOBL.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
503 NOBL.Low_Log Log of
504 NOBL.Low_mva200 200 Day MA
510 NOBL.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
513 NOBL.Close_mva200 200 Day MA
520 NOBL.Volume_SmoothDer Derivative of Smoothed
528 NOBL.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
531 NOBL.Adjusted_mva200 200 Day MA
537 SCHD.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
539 SCHD.Open_Log Log of
540 SCHD.Open_mva200 200 Day MA
546 SCHD.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
548 SCHD.High_Log Log of
549 SCHD.High_mva200 200 Day MA
555 SCHD.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
557 SCHD.Low_Log Log of
558 SCHD.Low_mva200 200 Day MA
564 SCHD.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
567 SCHD.Close_mva200 200 Day MA
582 SCHD.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
585 SCHD.Adjusted_mva200 200 Day MA
594 PFF.Open_mva200 200 Day MA
597 PFF.High_YoY4 4 Year over 4 Year
603 PFF.High_mva200 200 Day MA
606 PFF.Low_YoY4 4 Year over 4 Year
612 PFF.Low_mva200 200 Day MA
615 PFF.Close_YoY4 4 Year over 4 Year
621 PFF.Close_mva200 200 Day MA
626 PFF.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
628 PFF.Volume_SmoothDer Derivative of Smoothed
631 PFF.Volume_mva050 50 Day MA
633 PFF.Adjusted_YoY4 4 Year over 4 Year
636 PFF.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
638 PFF.Adjusted_Log Log of
639 PFF.Adjusted_mva200 200 Day MA
645 HPI.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
647 HPI.Open_Log Log of
648 HPI.Open_mva200 200 Day MA
656 HPI.High_Log Log of
657 HPI.High_mva200 200 Day MA
663 HPI.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
666 HPI.Low_mva200 200 Day MA
672 HPI.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
675 HPI.Close_mva200 200 Day MA
682 HPI.Volume_SmoothDer Derivative of Smoothed
690 HPI.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
693 HPI.Adjusted_mva200 200 Day MA
694 HPI.Adjusted_mva050 50 Day MA
699 GSFTX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
701 GSFTX.Open_Log Log of
702 GSFTX.Open_mva200 200 Day MA
708 GSFTX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
710 GSFTX.High_Log Log of
711 GSFTX.High_mva200 200 Day MA
717 GSFTX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
719 GSFTX.Low_Log Log of
720 GSFTX.Low_mva200 200 Day MA
726 GSFTX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
728 GSFTX.Close_Log Log of
729 GSFTX.Close_mva200 200 Day MA
731 GSFTX.Volume_YoY Year over Year
732 GSFTX.Volume_YoY4 4 Year over 4 Year
733 GSFTX.Volume_YoY5 5 Year over 5 Year
734 GSFTX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
735 GSFTX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
736 GSFTX.Volume_SmoothDer Derivative of Smoothed
737 GSFTX.Volume_Log Log of
738 GSFTX.Volume_mva200 200 Day MA
739 GSFTX.Volume_mva050 50 Day MA
744 GSFTX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
746 GSFTX.Adjusted_Log Log of
747 GSFTX.Adjusted_mva200 200 Day MA
785 LFMIX.Volume_YoY Year over Year
786 LFMIX.Volume_YoY4 4 Year over 4 Year
787 LFMIX.Volume_YoY5 5 Year over 5 Year
788 LFMIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
789 LFMIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
790 LFMIX.Volume_SmoothDer Derivative of Smoothed
791 LFMIX.Volume_Log Log of
792 LFMIX.Volume_mva200 200 Day MA
793 LFMIX.Volume_mva050 50 Day MA
839 LFMCX.Volume_YoY Year over Year
840 LFMCX.Volume_YoY4 4 Year over 4 Year
841 LFMCX.Volume_YoY5 5 Year over 5 Year
842 LFMCX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
843 LFMCX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
844 LFMCX.Volume_SmoothDer Derivative of Smoothed
845 LFMCX.Volume_Log Log of
846 LFMCX.Volume_mva200 200 Day MA
847 LFMCX.Volume_mva050 50 Day MA
893 LFMAX.Volume_YoY Year over Year
894 LFMAX.Volume_YoY4 4 Year over 4 Year
895 LFMAX.Volume_YoY5 5 Year over 5 Year
896 LFMAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
897 LFMAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
898 LFMAX.Volume_SmoothDer Derivative of Smoothed
899 LFMAX.Volume_Log Log of
900 LFMAX.Volume_mva200 200 Day MA
901 LFMAX.Volume_mva050 50 Day MA
914 LCSIX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
916 LCSIX.Open_SmoothDer Derivative of Smoothed
918 LCSIX.Open_mva200 200 Day MA
919 LCSIX.Open_mva050 50 Day MA
923 LCSIX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
925 LCSIX.High_SmoothDer Derivative of Smoothed
927 LCSIX.High_mva200 200 Day MA
928 LCSIX.High_mva050 50 Day MA
932 LCSIX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
934 LCSIX.Low_SmoothDer Derivative of Smoothed
936 LCSIX.Low_mva200 200 Day MA
937 LCSIX.Low_mva050 50 Day MA
941 LCSIX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
943 LCSIX.Close_SmoothDer Derivative of Smoothed
945 LCSIX.Close_mva200 200 Day MA
946 LCSIX.Close_mva050 50 Day MA
947 LCSIX.Volume_YoY Year over Year
948 LCSIX.Volume_YoY4 4 Year over 4 Year
949 LCSIX.Volume_YoY5 5 Year over 5 Year
950 LCSIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
951 LCSIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
952 LCSIX.Volume_SmoothDer Derivative of Smoothed
953 LCSIX.Volume_Log Log of
954 LCSIX.Volume_mva200 200 Day MA
955 LCSIX.Volume_mva050 50 Day MA
959 LCSIX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
963 LCSIX.Adjusted_mva200 200 Day MA
964 LCSIX.Adjusted_mva050 50 Day MA
1055 VBIRX.Volume_YoY Year over Year
1056 VBIRX.Volume_YoY4 4 Year over 4 Year
1057 VBIRX.Volume_YoY5 5 Year over 5 Year
1058 VBIRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1059 VBIRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1060 VBIRX.Volume_SmoothDer Derivative of Smoothed
1061 VBIRX.Volume_Log Log of
1062 VBIRX.Volume_mva200 200 Day MA
1063 VBIRX.Volume_mva050 50 Day MA
1078 BIV.Open_SmoothDer Derivative of Smoothed
1087 BIV.High_SmoothDer Derivative of Smoothed
1096 BIV.Low_SmoothDer Derivative of Smoothed
1105 BIV.Close_SmoothDer Derivative of Smoothed
1114 BIV.Volume_SmoothDer Derivative of Smoothed
1123 BIV.Adjusted_SmoothDer Derivative of Smoothed
1163 VFSUX.Volume_YoY Year over Year
1164 VFSUX.Volume_YoY4 4 Year over 4 Year
1165 VFSUX.Volume_YoY5 5 Year over 5 Year
1166 VFSUX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1167 VFSUX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1168 VFSUX.Volume_SmoothDer Derivative of Smoothed
1169 VFSUX.Volume_Log Log of
1170 VFSUX.Volume_mva200 200 Day MA
1171 VFSUX.Volume_mva050 50 Day MA
1179 VFSUX.Adjusted_mva200 200 Day MA
1186 LTUIX.Open_SmoothDer Derivative of Smoothed
1195 LTUIX.High_SmoothDer Derivative of Smoothed
1204 LTUIX.Low_SmoothDer Derivative of Smoothed
1213 LTUIX.Close_SmoothDer Derivative of Smoothed
1217 LTUIX.Volume_YoY Year over Year
1218 LTUIX.Volume_YoY4 4 Year over 4 Year
1219 LTUIX.Volume_YoY5 5 Year over 5 Year
1220 LTUIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1221 LTUIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1222 LTUIX.Volume_SmoothDer Derivative of Smoothed
1223 LTUIX.Volume_Log Log of
1224 LTUIX.Volume_mva200 200 Day MA
1225 LTUIX.Volume_mva050 50 Day MA
1231 LTUIX.Adjusted_SmoothDer Derivative of Smoothed
1240 PTTPX.Open_SmoothDer Derivative of Smoothed
1249 PTTPX.High_SmoothDer Derivative of Smoothed
1258 PTTPX.Low_SmoothDer Derivative of Smoothed
1267 PTTPX.Close_SmoothDer Derivative of Smoothed
1271 PTTPX.Volume_YoY Year over Year
1272 PTTPX.Volume_YoY4 4 Year over 4 Year
1273 PTTPX.Volume_YoY5 5 Year over 5 Year
1274 PTTPX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1275 PTTPX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1276 PTTPX.Volume_SmoothDer Derivative of Smoothed
1277 PTTPX.Volume_Log Log of
1278 PTTPX.Volume_mva200 200 Day MA
1279 PTTPX.Volume_mva050 50 Day MA
1285 PTTPX.Adjusted_SmoothDer Derivative of Smoothed
1287 PTTPX.Adjusted_mva200 200 Day MA
1294 NERYX.Open_SmoothDer Derivative of Smoothed
1303 NERYX.High_SmoothDer Derivative of Smoothed
1312 NERYX.Low_SmoothDer Derivative of Smoothed
1321 NERYX.Close_SmoothDer Derivative of Smoothed
1325 NERYX.Volume_YoY Year over Year
1326 NERYX.Volume_YoY4 4 Year over 4 Year
1327 NERYX.Volume_YoY5 5 Year over 5 Year
1328 NERYX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1329 NERYX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1330 NERYX.Volume_SmoothDer Derivative of Smoothed
1331 NERYX.Volume_Log Log of
1332 NERYX.Volume_mva200 200 Day MA
1333 NERYX.Volume_mva050 50 Day MA
1339 NERYX.Adjusted_SmoothDer Derivative of Smoothed
1341 NERYX.Adjusted_mva200 200 Day MA
1348 STIGX.Open_SmoothDer Derivative of Smoothed
1357 STIGX.High_SmoothDer Derivative of Smoothed
1366 STIGX.Low_SmoothDer Derivative of Smoothed
1375 STIGX.Close_SmoothDer Derivative of Smoothed
1379 STIGX.Volume_YoY Year over Year
1380 STIGX.Volume_YoY4 4 Year over 4 Year
1381 STIGX.Volume_YoY5 5 Year over 5 Year
1382 STIGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1383 STIGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1384 STIGX.Volume_SmoothDer Derivative of Smoothed
1385 STIGX.Volume_Log Log of
1386 STIGX.Volume_mva200 200 Day MA
1387 STIGX.Volume_mva050 50 Day MA
1393 STIGX.Adjusted_SmoothDer Derivative of Smoothed
1395 STIGX.Adjusted_mva200 200 Day MA
1402 HLGAX.Open_SmoothDer Derivative of Smoothed
1411 HLGAX.High_SmoothDer Derivative of Smoothed
1420 HLGAX.Low_SmoothDer Derivative of Smoothed
1429 HLGAX.Close_SmoothDer Derivative of Smoothed
1433 HLGAX.Volume_YoY Year over Year
1434 HLGAX.Volume_YoY4 4 Year over 4 Year
1435 HLGAX.Volume_YoY5 5 Year over 5 Year
1436 HLGAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1437 HLGAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1438 HLGAX.Volume_SmoothDer Derivative of Smoothed
1439 HLGAX.Volume_Log Log of
1440 HLGAX.Volume_mva200 200 Day MA
1441 HLGAX.Volume_mva050 50 Day MA
1447 HLGAX.Adjusted_SmoothDer Derivative of Smoothed
1456 FTRGX.Open_SmoothDer Derivative of Smoothed
1465 FTRGX.High_SmoothDer Derivative of Smoothed
1474 FTRGX.Low_SmoothDer Derivative of Smoothed
1483 FTRGX.Close_SmoothDer Derivative of Smoothed
1487 FTRGX.Volume_YoY Year over Year
1488 FTRGX.Volume_YoY4 4 Year over 4 Year
1489 FTRGX.Volume_YoY5 5 Year over 5 Year
1490 FTRGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1491 FTRGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1492 FTRGX.Volume_SmoothDer Derivative of Smoothed
1493 FTRGX.Volume_Log Log of
1494 FTRGX.Volume_mva200 200 Day MA
1495 FTRGX.Volume_mva050 50 Day MA
1501 FTRGX.Adjusted_SmoothDer Derivative of Smoothed
1510 THIIX.Open_SmoothDer Derivative of Smoothed
1519 THIIX.High_SmoothDer Derivative of Smoothed
1528 THIIX.Low_SmoothDer Derivative of Smoothed
1537 THIIX.Close_SmoothDer Derivative of Smoothed
1541 THIIX.Volume_YoY Year over Year
1542 THIIX.Volume_YoY4 4 Year over 4 Year
1543 THIIX.Volume_YoY5 5 Year over 5 Year
1544 THIIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1545 THIIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1546 THIIX.Volume_SmoothDer Derivative of Smoothed
1547 THIIX.Volume_Log Log of
1548 THIIX.Volume_mva200 200 Day MA
1549 THIIX.Volume_mva050 50 Day MA
1555 THIIX.Adjusted_SmoothDer Derivative of Smoothed
1557 THIIX.Adjusted_mva200 200 Day MA
1564 PTTRX.Open_SmoothDer Derivative of Smoothed
1573 PTTRX.High_SmoothDer Derivative of Smoothed
1582 PTTRX.Low_SmoothDer Derivative of Smoothed
1591 PTTRX.Close_SmoothDer Derivative of Smoothed
1595 PTTRX.Volume_YoY Year over Year
1596 PTTRX.Volume_YoY4 4 Year over 4 Year
1597 PTTRX.Volume_YoY5 5 Year over 5 Year
1598 PTTRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1599 PTTRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1600 PTTRX.Volume_SmoothDer Derivative of Smoothed
1601 PTTRX.Volume_Log Log of
1602 PTTRX.Volume_mva200 200 Day MA
1603 PTTRX.Volume_mva050 50 Day MA
1609 PTTRX.Adjusted_SmoothDer Derivative of Smoothed
1611 PTTRX.Adjusted_mva200 200 Day MA
1618 BFIGX.Open_SmoothDer Derivative of Smoothed
1620 BFIGX.Open_mva200 200 Day MA
1627 BFIGX.High_SmoothDer Derivative of Smoothed
1629 BFIGX.High_mva200 200 Day MA
1636 BFIGX.Low_SmoothDer Derivative of Smoothed
1638 BFIGX.Low_mva200 200 Day MA
1645 BFIGX.Close_SmoothDer Derivative of Smoothed
1647 BFIGX.Close_mva200 200 Day MA
1649 BFIGX.Volume_YoY Year over Year
1650 BFIGX.Volume_YoY4 4 Year over 4 Year
1651 BFIGX.Volume_YoY5 5 Year over 5 Year
1652 BFIGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1653 BFIGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1654 BFIGX.Volume_SmoothDer Derivative of Smoothed
1655 BFIGX.Volume_Log Log of
1656 BFIGX.Volume_mva200 200 Day MA
1657 BFIGX.Volume_mva050 50 Day MA
1661 BFIGX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1663 BFIGX.Adjusted_SmoothDer Derivative of Smoothed
1665 BFIGX.Adjusted_mva200 200 Day MA
1670 VTWO.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1671 VTWO.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1673 VTWO.Open_Log Log of
1674 VTWO.Open_mva200 200 Day MA
1679 VTWO.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1680 VTWO.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1682 VTWO.High_Log Log of
1683 VTWO.High_mva200 200 Day MA
1688 VTWO.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1689 VTWO.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1691 VTWO.Low_Log Log of
1692 VTWO.Low_mva200 200 Day MA
1697 VTWO.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1698 VTWO.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1701 VTWO.Close_mva200 200 Day MA
1706 VTWO.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1710 VTWO.Volume_mva200 200 Day MA
1715 VTWO.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1716 VTWO.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1719 VTWO.Adjusted_mva200 200 Day MA
1724 EIFAX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1728 EIFAX.Open_mva200 200 Day MA
1733 EIFAX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1737 EIFAX.High_mva200 200 Day MA
1742 EIFAX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1746 EIFAX.Low_mva200 200 Day MA
1751 EIFAX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1755 EIFAX.Close_mva200 200 Day MA
1757 EIFAX.Volume_YoY Year over Year
1758 EIFAX.Volume_YoY4 4 Year over 4 Year
1759 EIFAX.Volume_YoY5 5 Year over 5 Year
1760 EIFAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1761 EIFAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1762 EIFAX.Volume_SmoothDer Derivative of Smoothed
1763 EIFAX.Volume_Log Log of
1764 EIFAX.Volume_mva200 200 Day MA
1765 EIFAX.Volume_mva050 50 Day MA
1769 EIFAX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1773 EIFAX.Adjusted_mva200 200 Day MA
1774 EIFAX.Adjusted_mva050 50 Day MA
1811 ASDAX.Volume_YoY Year over Year
1812 ASDAX.Volume_YoY4 4 Year over 4 Year
1813 ASDAX.Volume_YoY5 5 Year over 5 Year
1814 ASDAX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1815 ASDAX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1816 ASDAX.Volume_SmoothDer Derivative of Smoothed
1817 ASDAX.Volume_Log Log of
1818 ASDAX.Volume_mva200 200 Day MA
1819 ASDAX.Volume_mva050 50 Day MA
1823 ASDAX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1827 ASDAX.Adjusted_mva200 200 Day MA
1865 TRBUX.Volume_YoY Year over Year
1866 TRBUX.Volume_YoY4 4 Year over 4 Year
1867 TRBUX.Volume_YoY5 5 Year over 5 Year
1868 TRBUX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1869 TRBUX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1870 TRBUX.Volume_SmoothDer Derivative of Smoothed
1871 TRBUX.Volume_Log Log of
1872 TRBUX.Volume_mva200 200 Day MA
1873 TRBUX.Volume_mva050 50 Day MA
1887 PRWCX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1888 PRWCX.Open_SmoothDer Derivative of Smoothed
1889 PRWCX.Open_Log Log of
1890 PRWCX.Open_mva200 200 Day MA
1891 PRWCX.Open_mva050 50 Day MA
1896 PRWCX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1897 PRWCX.High_SmoothDer Derivative of Smoothed
1898 PRWCX.High_Log Log of
1899 PRWCX.High_mva200 200 Day MA
1900 PRWCX.High_mva050 50 Day MA
1905 PRWCX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1906 PRWCX.Low_SmoothDer Derivative of Smoothed
1907 PRWCX.Low_Log Log of
1908 PRWCX.Low_mva200 200 Day MA
1909 PRWCX.Low_mva050 50 Day MA
1914 PRWCX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1915 PRWCX.Close_SmoothDer Derivative of Smoothed
1916 PRWCX.Close_Log Log of
1917 PRWCX.Close_mva200 200 Day MA
1918 PRWCX.Close_mva050 50 Day MA
1919 PRWCX.Volume_YoY Year over Year
1920 PRWCX.Volume_YoY4 4 Year over 4 Year
1921 PRWCX.Volume_YoY5 5 Year over 5 Year
1922 PRWCX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1923 PRWCX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1924 PRWCX.Volume_SmoothDer Derivative of Smoothed
1925 PRWCX.Volume_Log Log of
1926 PRWCX.Volume_mva200 200 Day MA
1927 PRWCX.Volume_mva050 50 Day MA
1931 PRWCX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1932 PRWCX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1934 PRWCX.Adjusted_Log Log of
1935 PRWCX.Adjusted_mva200 200 Day MA
1936 PRWCX.Adjusted_mva050 50 Day MA
1940 ADOZX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1942 ADOZX.Open_SmoothDer Derivative of Smoothed
1944 ADOZX.Open_mva200 200 Day MA
1949 ADOZX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1951 ADOZX.High_SmoothDer Derivative of Smoothed
1953 ADOZX.High_mva200 200 Day MA
1958 ADOZX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1960 ADOZX.Low_SmoothDer Derivative of Smoothed
1962 ADOZX.Low_mva200 200 Day MA
1967 ADOZX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1969 ADOZX.Close_SmoothDer Derivative of Smoothed
1971 ADOZX.Close_mva200 200 Day MA
1973 ADOZX.Volume_YoY Year over Year
1974 ADOZX.Volume_YoY4 4 Year over 4 Year
1975 ADOZX.Volume_YoY5 5 Year over 5 Year
1976 ADOZX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1977 ADOZX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
1978 ADOZX.Volume_SmoothDer Derivative of Smoothed
1979 ADOZX.Volume_Log Log of
1980 ADOZX.Volume_mva200 200 Day MA
1981 ADOZX.Volume_mva050 50 Day MA
1985 ADOZX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
1987 ADOZX.Adjusted_SmoothDer Derivative of Smoothed
1989 ADOZX.Adjusted_mva200 200 Day MA
2027 MERFX.Volume_YoY Year over Year
2028 MERFX.Volume_YoY4 4 Year over 4 Year
2029 MERFX.Volume_YoY5 5 Year over 5 Year
2030 MERFX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2031 MERFX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2032 MERFX.Volume_SmoothDer Derivative of Smoothed
2033 MERFX.Volume_Log Log of
2034 MERFX.Volume_mva200 200 Day MA
2035 MERFX.Volume_mva050 50 Day MA
2046 CMNIX.Open_YoY4 4 Year over 4 Year
2048 CMNIX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2049 CMNIX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2051 CMNIX.Open_Log Log of
2052 CMNIX.Open_mva200 200 Day MA
2053 CMNIX.Open_mva050 50 Day MA
2055 CMNIX.High_YoY4 4 Year over 4 Year
2057 CMNIX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2058 CMNIX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2060 CMNIX.High_Log Log of
2061 CMNIX.High_mva200 200 Day MA
2062 CMNIX.High_mva050 50 Day MA
2064 CMNIX.Low_YoY4 4 Year over 4 Year
2066 CMNIX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2067 CMNIX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2069 CMNIX.Low_Log Log of
2070 CMNIX.Low_mva200 200 Day MA
2071 CMNIX.Low_mva050 50 Day MA
2073 CMNIX.Close_YoY4 4 Year over 4 Year
2075 CMNIX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2076 CMNIX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2078 CMNIX.Close_Log Log of
2079 CMNIX.Close_mva200 200 Day MA
2080 CMNIX.Close_mva050 50 Day MA
2081 CMNIX.Volume_YoY Year over Year
2082 CMNIX.Volume_YoY4 4 Year over 4 Year
2083 CMNIX.Volume_YoY5 5 Year over 5 Year
2084 CMNIX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2085 CMNIX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2086 CMNIX.Volume_SmoothDer Derivative of Smoothed
2087 CMNIX.Volume_Log Log of
2088 CMNIX.Volume_mva200 200 Day MA
2089 CMNIX.Volume_mva050 50 Day MA
2091 CMNIX.Adjusted_YoY4 4 Year over 4 Year
2093 CMNIX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2094 CMNIX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2096 CMNIX.Adjusted_Log Log of
2097 CMNIX.Adjusted_mva200 200 Day MA
2098 CMNIX.Adjusted_mva050 50 Day MA
2103 CIHEX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2105 CIHEX.Open_Log Log of
2106 CIHEX.Open_mva200 200 Day MA
2107 CIHEX.Open_mva050 50 Day MA
2112 CIHEX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2114 CIHEX.High_Log Log of
2115 CIHEX.High_mva200 200 Day MA
2116 CIHEX.High_mva050 50 Day MA
2121 CIHEX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2123 CIHEX.Low_Log Log of
2124 CIHEX.Low_mva200 200 Day MA
2125 CIHEX.Low_mva050 50 Day MA
2130 CIHEX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2132 CIHEX.Close_Log Log of
2133 CIHEX.Close_mva200 200 Day MA
2134 CIHEX.Close_mva050 50 Day MA
2135 CIHEX.Volume_YoY Year over Year
2136 CIHEX.Volume_YoY4 4 Year over 4 Year
2137 CIHEX.Volume_YoY5 5 Year over 5 Year
2138 CIHEX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2139 CIHEX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2140 CIHEX.Volume_SmoothDer Derivative of Smoothed
2141 CIHEX.Volume_Log Log of
2142 CIHEX.Volume_mva200 200 Day MA
2143 CIHEX.Volume_mva050 50 Day MA
2147 CIHEX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2148 CIHEX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2150 CIHEX.Adjusted_Log Log of
2151 CIHEX.Adjusted_mva200 200 Day MA
2152 CIHEX.Adjusted_mva050 50 Day MA
2156 IMPCH_Smooth Savitsky-Golay Smoothed (p=3, n=365) U.S. Imports of Goods by Customs Basis from China (Monthly, NSA)
2158 IMPCH_SmoothDer Derivative of Smoothed U.S. Imports of Goods by Customs Basis from China (Monthly, NSA)
2159 IMPCH_Log Log of U.S. Imports of Goods by Customs Basis from China (Monthly, NSA)
2160 IMPCH_mva200 U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 200 Day MA
2161 IMPCH_mva050 U.S. Imports of Goods by Customs Basis from China (Monthly, NSA) 50 Day MA
2167 EXPCH_SmoothDer Derivative of Smoothed U.S. Exports of Goods by F.A.S. Basis to China, Mainland (Monthly, NSA)
2191 HSN1FNSA_YoY5 New One Family Houses Sold: United States (Monthly, NSA) 5 Year over 5 Year
2192 HSN1FNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) New One Family Houses Sold: United States (Monthly, NSA)
2195 HSN1FNSA_Log Log of New One Family Houses Sold: United States (Monthly, NSA)
2204 HNFSUSNSA_Log Log of New One Family Houses for Sale in the United States (Monthly, NSA)
2205 HNFSUSNSA_mva200 New One Family Houses for Sale in the United States (Monthly, NSA) 200 Day MA
2206 HNFSUSNSA_mva050 New One Family Houses for Sale in the United States (Monthly, NSA) 50 Day MA
2207 BUSLOANS_YoY Commercial and Industrial Loans, All Commercial Banks (Monthly, SA) Year over Year
2216 TOTCI_YoY Commercial and Industrial Loans, All Commercial Banks (Weekly, SA) Year over Year
2225 BUSLOANSNSA_YoY Commercial and Industrial Loans, All Commercial Banks (Monthly, NSA) Year over Year
2234 REALLNNSA_YoY Real Estate Loans, All Commercial Banks (Monthly, NSA) Year over Year
2237 REALLNNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Monthly, NSA)
2239 REALLNNSA_SmoothDer Derivative of Smoothed Real Estate Loans, All Commercial Banks (Monthly, NSA)
2240 REALLNNSA_Log Log of Real Estate Loans, All Commercial Banks (Monthly, NSA)
2241 REALLNNSA_mva200 Real Estate Loans, All Commercial Banks (Monthly, NSA) 200 Day MA
2242 REALLNNSA_mva050 Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2243 REALLN_YoY Real Estate Loans, All Commercial Banks (Monthly, SA) Year over Year
2246 REALLN_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Monthly, SA)
2248 REALLN_SmoothDer Derivative of Smoothed Real Estate Loans, All Commercial Banks (Monthly, SA)
2249 REALLN_Log Log of Real Estate Loans, All Commercial Banks (Monthly, SA)
2250 REALLN_mva200 Real Estate Loans, All Commercial Banks (Monthly, SA) 200 Day MA
2251 REALLN_mva050 Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2255 RELACBW027NBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, NSA)
2257 RELACBW027NBOG_SmoothDer Derivative of Smoothed Real Estate Loans, All Commercial Banks (Weekly, NSA)
2259 RELACBW027NBOG_mva200 Real Estate Loans, All Commercial Banks (Weekly, NSA) 200 Day MA
2260 RELACBW027NBOG_mva050 Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2261 RELACBW027SBOG_YoY Real Estate Loans, All Commercial Banks (Weekly, SA) Year over Year
2264 RELACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans, All Commercial Banks (Weekly, SA)
2266 RELACBW027SBOG_SmoothDer Derivative of Smoothed Real Estate Loans, All Commercial Banks (Weekly, SA)
2267 RELACBW027SBOG_Log Log of Real Estate Loans, All Commercial Banks (Weekly, SA)
2268 RELACBW027SBOG_mva200 Real Estate Loans, All Commercial Banks (Weekly, SA) 200 Day MA
2269 RELACBW027SBOG_mva050 Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2270 RREACBM027NBOG_YoY Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) Year over Year
2273 RREACBM027NBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2275 RREACBM027NBOG_SmoothDer Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2276 RREACBM027NBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA)
2278 RREACBM027NBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, NSA) 50 Day MA
2279 RREACBM027SBOG_YoY Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) Year over Year
2282 RREACBM027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2284 RREACBM027SBOG_SmoothDer Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2285 RREACBM027SBOG_Log Log of Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA)
2287 RREACBM027SBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Monthly, SA) 50 Day MA
2288 RREACBW027SBOG_YoY Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) Year over Year
2291 RREACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2293 RREACBW027SBOG_SmoothDer Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA)
2296 RREACBW027SBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, SA) 50 Day MA
2300 RREACBW027NBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
2302 RREACBW027NBOG_SmoothDer Derivative of Smoothed Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA)
2305 RREACBW027NBOG_mva050 Real Estate Loans: Residential Real Estate Loans, All Commercial Banks (Weekly, NSA) 50 Day MA
2309 MORTGAGE30US_Smooth Savitsky-Golay Smoothed (p=3, n=365) 30-Year Fixed Rate Mortgage Average in the United States
2320 CONSUMERNSA_SmoothDer Derivative of Smoothed Consumer Loans, All Commercial Banks
2321 CONSUMERNSA_Log Log of Consumer Loans, All Commercial Banks
2322 CONSUMERNSA_mva200 Consumer Loans, All Commercial Banks 200 Day MA
2323 CONSUMERNSA_mva050 Consumer Loans, All Commercial Banks 50 Day MA
2327 TOTLLNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Loans and Leases in Bank Credit, All Commercial Banks
2329 TOTLLNSA_SmoothDer Derivative of Smoothed Loans and Leases in Bank Credit, All Commercial Banks
2331 TOTLLNSA_mva200 Loans and Leases in Bank Credit, All Commercial Banks 200 Day MA
2332 TOTLLNSA_mva050 Loans and Leases in Bank Credit, All Commercial Banks 50 Day MA
2336 DPSACBW027SBOG_Smooth Savitsky-Golay Smoothed (p=3, n=365) Deposits, All Commercial Banks
2339 DPSACBW027SBOG_Log Log of Deposits, All Commercial Banks
2340 DPSACBW027SBOG_mva200 Deposits, All Commercial Banks 200 Day MA
2341 DPSACBW027SBOG_mva050 Deposits, All Commercial Banks 50 Day MA
2342 DRCLACBS_YoY Delinquency Rate on Consumer Loans, All Commercial Banks, SA Year over Year
2347 DRCLACBS_SmoothDer Derivative of Smoothed Delinquency Rate on Consumer Loans, All Commercial Banks, SA
2348 DRCLACBS_Log Log of Delinquency Rate on Consumer Loans, All Commercial Banks, SA
2351 TOTCINSA_YoY Commercial and Industrial Loans, All Commercial Banks (Weekly, NSA) Year over Year
2361 SRPSABSNNCB_YoY4 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 4 Year over 4 Year
2366 SRPSABSNNCB_Log Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA)
2367 SRPSABSNNCB_mva200 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 200 Day MA
2368 SRPSABSNNCB_mva050 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) 50 Day MA
2375 ASTLL_Log Log of All sectors; total loans; liability, Level (NSA)
2376 ASTLL_mva200 All sectors; total loans; liability, Level (NSA) 200 Day MA
2377 ASTLL_mva050 All sectors; total loans; liability, Level (NSA) 50 Day MA
2381 FBDILNECA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2383 FBDILNECA_SmoothDer Derivative of Smoothed Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2384 FBDILNECA_Log Log of Domestic financial sectors; depository institution loans n.e.c.; asset, Level (NSA)
2390 ASOLAL_Smooth Savitsky-Golay Smoothed (p=3, n=365) All sectors; other loans and advances; liability, Level (NSA)
2393 ASOLAL_Log Log of All sectors; other loans and advances; liability, Level (NSA)
2394 ASOLAL_mva200 All sectors; other loans and advances; liability, Level (NSA) 200 Day MA
2395 ASOLAL_mva050 All sectors; other loans and advances; liability, Level (NSA) 50 Day MA
2402 ASTMA_Log Log of All sectors; total mortgages; asset, Level (NSA)
2403 ASTMA_mva200 All sectors; total mortgages; asset, Level (NSA) 200 Day MA
2404 ASTMA_mva050 All sectors; total mortgages; asset, Level (NSA) 50 Day MA
2411 ASHMA_Log Log of All sectors; home mortgages; asset, Level (NSA)
2412 ASHMA_mva200 All sectors; home mortgages; asset, Level (NSA) 200 Day MA
2413 ASHMA_mva050 All sectors; home mortgages; asset, Level (NSA) 50 Day MA
2420 ASMRMA_Log Log of All sectors; multifamily residential mortgages; asset, Level (NSA)
2421 ASMRMA_mva200 All sectors; multifamily residential mortgages; asset, Level (NSA) 200 Day MA
2422 ASMRMA_mva050 All sectors; multifamily residential mortgages; asset, Level (NSA) 50 Day MA
2429 ASCMA_Log Log of All sectors; commercial mortgages; asset, Level (NSA)
2430 ASCMA_mva200 All sectors; commercial mortgages; asset, Level (NSA) 200 Day MA
2431 ASCMA_mva050 All sectors; commercial mortgages; asset, Level (NSA) 50 Day MA
2438 ASFMA_Log Log of All sectors; farm mortgages; asset, Level (NSA)
2439 ASFMA_mva200 All sectors; farm mortgages; asset, Level (NSA) 200 Day MA
2440 ASFMA_mva050 All sectors; farm mortgages; asset, Level (NSA) 50 Day MA
2447 CCLBSHNO_Log Log of Households and nonprofit organizations; consumer credit; liability, Level (NSA)
2448 CCLBSHNO_mva200 Households and nonprofit organizations; consumer credit; liability, Level (NSA) 200 Day MA
2449 CCLBSHNO_mva050 Households and nonprofit organizations; consumer credit; liability, Level (NSA) 50 Day MA
2456 FBDSILQ027S_Log Log of Domestic financial sectors debt securities; liability, Level (NSA)
2457 FBDSILQ027S_mva200 Domestic financial sectors debt securities; liability, Level (NSA) 200 Day MA
2458 FBDSILQ027S_mva050 Domestic financial sectors debt securities; liability, Level (NSA) 50 Day MA
2460 FBLL_YoY4 Domestic financial sectors loans; liability, Level (NSA) 4 Year over 4 Year
2461 FBLL_YoY5 Domestic financial sectors loans; liability, Level (NSA) 5 Year over 5 Year
2465 FBLL_Log Log of Domestic financial sectors loans; liability, Level (NSA)
2466 FBLL_mva200 Domestic financial sectors loans; liability, Level (NSA) 200 Day MA
2467 FBLL_mva050 Domestic financial sectors loans; liability, Level (NSA) 50 Day MA
2471 NCBDBIQ027S_Smooth Savitsky-Golay Smoothed (p=3, n=365) Nonfinancial corporate business; debt securities; liability, Level
2474 NCBDBIQ027S_Log Log of Nonfinancial corporate business; debt securities; liability, Level
2475 NCBDBIQ027S_mva200 Nonfinancial corporate business; debt securities; liability, Level 200 Day MA
2476 NCBDBIQ027S_mva050 Nonfinancial corporate business; debt securities; liability, Level 50 Day MA
2480 DGS10_Smooth Savitsky-Golay Smoothed (p=3, n=365) 10-Year Treasury Constant Maturity Rate
2489 TNX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2498 TNX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2507 TNX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2516 TNX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2522 TNX.Volume_YoY Year over Year
2523 TNX.Volume_YoY4 4 Year over 4 Year
2524 TNX.Volume_YoY5 5 Year over 5 Year
2525 TNX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2526 TNX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2527 TNX.Volume_SmoothDer Derivative of Smoothed
2528 TNX.Volume_Log Log of
2529 TNX.Volume_mva200 200 Day MA
2530 TNX.Volume_mva050 50 Day MA
2534 TNX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2542 CLF.Open_YoY5 5 Year over 5 Year
2543 CLF.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2546 CLF.Open_Log Log of
2547 CLF.Open_mva200 200 Day MA
2548 CLF.Open_mva050 50 Day MA
2552 CLF.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2556 CLF.High_mva200 200 Day MA
2557 CLF.High_mva050 50 Day MA
2561 CLF.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2564 CLF.Low_Log Log of
2565 CLF.Low_mva200 200 Day MA
2566 CLF.Low_mva050 50 Day MA
2570 CLF.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2573 CLF.Close_Log Log of
2574 CLF.Close_mva200 200 Day MA
2575 CLF.Close_mva050 50 Day MA
2579 CLF.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2582 CLF.Volume_Log Log of
2588 CLF.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2591 CLF.Adjusted_Log Log of
2592 CLF.Adjusted_mva200 200 Day MA
2593 CLF.Adjusted_mva050 50 Day MA
2603 DGS1_YoY 1-Year Treasury Constant Maturity Rate Year over Year
2606 DGS1_Smooth Savitsky-Golay Smoothed (p=3, n=365) 1-Year Treasury Constant Maturity Rate
2607 DGS1_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) 1-Year Treasury Constant Maturity Rate
2608 DGS1_SmoothDer Derivative of Smoothed 1-Year Treasury Constant Maturity Rate
2609 DGS1_Log Log of 1-Year Treasury Constant Maturity Rate
2611 DGS1_mva050 1-Year Treasury Constant Maturity Rate 50 Day MA
2615 DGS2_Smooth Savitsky-Golay Smoothed (p=3, n=365) 2-Year Treasury Constant Maturity Rate
2617 DGS2_SmoothDer Derivative of Smoothed 2-Year Treasury Constant Maturity Rate
2619 DGS2_mva200 2-Year Treasury Constant Maturity Rate 200 Day MA
2620 DGS2_mva050 2-Year Treasury Constant Maturity Rate 50 Day MA
2621 TB3MS_YoY 3-Month Treasury Bill: Secondary Market Rate (Monthly) Year over Year
2626 TB3MS_SmoothDer Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2627 TB3MS_Log Log of 3-Month Treasury Bill: Secondary Market Rate (Monthly)
2633 DTB3_Smooth Savitsky-Golay Smoothed (p=3, n=365) 3-Month Treasury Bill: Secondary Market Rate (Daily)
2635 DTB3_SmoothDer Derivative of Smoothed 3-Month Treasury Bill: Secondary Market Rate (Daily)
2636 DTB3_Log Log of 3-Month Treasury Bill: Secondary Market Rate (Daily)
2645 IRX.Open_Log Log of
2654 IRX.High_Log Log of
2660 IRX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2662 IRX.Low_SmoothDer Derivative of Smoothed
2663 IRX.Low_Log Log of
2669 IRX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2671 IRX.Close_SmoothDer Derivative of Smoothed
2672 IRX.Close_Log Log of
2675 IRX.Volume_YoY Year over Year
2676 IRX.Volume_YoY4 4 Year over 4 Year
2677 IRX.Volume_YoY5 5 Year over 5 Year
2678 IRX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2679 IRX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2680 IRX.Volume_SmoothDer Derivative of Smoothed
2681 IRX.Volume_Log Log of
2682 IRX.Volume_mva200 200 Day MA
2683 IRX.Volume_mva050 50 Day MA
2687 IRX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2689 IRX.Adjusted_SmoothDer Derivative of Smoothed
2690 IRX.Adjusted_Log Log of
2696 DCOILWTICO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2697 DCOILWTICO_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2699 DCOILWTICO_Log Log of Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma
2700 DCOILWTICO_mva200 Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma 200 Day MA
2701 DCOILWTICO_mva050 Crude Oil Prices: West Texas Intermediate (WTI) Cushing, Oklahoma 50 Day MA
2704 DCOILBRENTEU_YoY5 Crude Oil Prices: Brent - Europe 5 Year over 5 Year
2705 DCOILBRENTEU_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil Prices: Brent - Europe
2709 DCOILBRENTEU_mva200 Crude Oil Prices: Brent - Europe 200 Day MA
2710 DCOILBRENTEU_mva050 Crude Oil Prices: Brent - Europe 50 Day MA
2717 NEWORDER_Log Log of Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft
2718 NEWORDER_mva200 Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 200 Day MA
2719 NEWORDER_mva050 Manufacturers’ New Orders: Nondefense Capital Goods Excluding Aircraft 50 Day MA
2740 GSPC.Open_YoY5 5 Year over 5 Year
2741 GSPC.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2742 GSPC.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2744 GSPC.Open_Log Log of
2745 GSPC.Open_mva200 200 Day MA
2750 GSPC.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2751 GSPC.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2753 GSPC.High_Log Log of
2754 GSPC.High_mva200 200 Day MA
2758 GSPC.Low_YoY5 5 Year over 5 Year
2759 GSPC.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2760 GSPC.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2762 GSPC.Low_Log Log of
2763 GSPC.Low_mva200 200 Day MA
2768 GSPC.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2769 GSPC.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2771 GSPC.Close_Log Log of
2772 GSPC.Close_mva200 200 Day MA
2786 GSPC.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2787 GSPC.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2789 GSPC.Adjusted_Log Log of
2790 GSPC.Adjusted_mva200 200 Day MA
2794 RLG.Open_YoY5 5 Year over 5 Year
2795 RLG.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2796 RLG.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2797 RLG.Open_SmoothDer Derivative of Smoothed
2798 RLG.Open_Log Log of
2799 RLG.Open_mva200 200 Day MA
2803 RLG.High_YoY5 5 Year over 5 Year
2804 RLG.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2805 RLG.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2806 RLG.High_SmoothDer Derivative of Smoothed
2807 RLG.High_Log Log of
2808 RLG.High_mva200 200 Day MA
2812 RLG.Low_YoY5 5 Year over 5 Year
2813 RLG.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2814 RLG.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2815 RLG.Low_SmoothDer Derivative of Smoothed
2816 RLG.Low_Log Log of
2817 RLG.Low_mva200 200 Day MA
2821 RLG.Close_YoY5 5 Year over 5 Year
2822 RLG.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2823 RLG.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2824 RLG.Close_SmoothDer Derivative of Smoothed
2825 RLG.Close_Log Log of
2826 RLG.Close_mva200 200 Day MA
2828 RLG.Volume_YoY Year over Year
2829 RLG.Volume_YoY4 4 Year over 4 Year
2830 RLG.Volume_YoY5 5 Year over 5 Year
2831 RLG.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2832 RLG.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2833 RLG.Volume_SmoothDer Derivative of Smoothed
2834 RLG.Volume_Log Log of
2835 RLG.Volume_mva200 200 Day MA
2836 RLG.Volume_mva050 50 Day MA
2839 RLG.Adjusted_YoY5 5 Year over 5 Year
2840 RLG.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2841 RLG.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2842 RLG.Adjusted_SmoothDer Derivative of Smoothed
2843 RLG.Adjusted_Log Log of
2844 RLG.Adjusted_mva200 200 Day MA
2848 DJI.Open_YoY5 5 Year over 5 Year
2850 DJI.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2852 DJI.Open_Log Log of
2853 DJI.Open_mva200 200 Day MA
2859 DJI.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2862 DJI.High_mva200 200 Day MA
2868 DJI.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2870 DJI.Low_Log Log of
2871 DJI.Low_mva200 200 Day MA
2877 DJI.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2880 DJI.Close_mva200 200 Day MA
2885 DJI.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2887 DJI.Volume_SmoothDer Derivative of Smoothed
2895 DJI.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2898 DJI.Adjusted_mva200 200 Day MA
2904 STOXX50E.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2906 STOXX50E.Open_Log Log of
2907 STOXX50E.Open_mva200 200 Day MA
2913 STOXX50E.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2915 STOXX50E.High_Log Log of
2916 STOXX50E.High_mva200 200 Day MA
2922 STOXX50E.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2924 STOXX50E.Low_Log Log of
2925 STOXX50E.Low_mva200 200 Day MA
2931 STOXX50E.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2933 STOXX50E.Close_Log Log of
2934 STOXX50E.Close_mva200 200 Day MA
2939 STOXX50E.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2941 STOXX50E.Volume_SmoothDer Derivative of Smoothed
2942 STOXX50E.Volume_Log Log of
2944 STOXX50E.Volume_mva050 50 Day MA
2949 STOXX50E.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
2951 STOXX50E.Adjusted_Log Log of
2952 STOXX50E.Adjusted_mva200 200 Day MA
2961 EFA.Open_mva200 200 Day MA
2970 EFA.High_mva200 200 Day MA
2979 EFA.Low_mva200 200 Day MA
2988 EFA.Close_mva200 200 Day MA
2993 EFA.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
2995 EFA.Volume_SmoothDer Derivative of Smoothed
3006 EFA.Adjusted_mva200 200 Day MA
3014 GDP_Log Log of Gross Domestic Product
3015 GDP_mva200 Gross Domestic Product 200 Day MA
3016 GDP_mva050 Gross Domestic Product 50 Day MA
3031 FDEFX_SmoothDer Derivative of Smoothed Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3032 FDEFX_Log Log of Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate)
3033 FDEFX_mva200 Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate) 200 Day MA
3034 FDEFX_mva050 Federal Government: National Defense Consumption Expenditures and Gross Investment (SA, Annual Rate) 50 Day MA
3036 GDPNOW_YoY4 Fed Atlanta GDPNow 4 Year over 4 Year
3037 GDPNOW_YoY5 Fed Atlanta GDPNow 5 Year over 5 Year
3038 GDPNOW_Smooth Savitsky-Golay Smoothed (p=3, n=365) Fed Atlanta GDPNow
3041 GDPNOW_Log Log of Fed Atlanta GDPNow
3043 GDPNOW_mva050 Fed Atlanta GDPNow 50 Day MA
3050 GDPC1_Log Log of Real Gross Domestic Product
3051 GDPC1_mva200 Real Gross Domestic Product 200 Day MA
3052 GDPC1_mva050 Real Gross Domestic Product 50 Day MA
3059 GDPDEF_Log Log of Gross Domestic Product: Implicit Price Deflator
3060 GDPDEF_mva200 Gross Domestic Product: Implicit Price Deflator 200 Day MA
3061 GDPDEF_mva050 Gross Domestic Product: Implicit Price Deflator 50 Day MA
3064 VIG.Open_YoY5 5 Year over 5 Year
3066 VIG.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3068 VIG.Open_Log Log of
3069 VIG.Open_mva200 200 Day MA
3075 VIG.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3077 VIG.High_Log Log of
3078 VIG.High_mva200 200 Day MA
3082 VIG.Low_YoY5 5 Year over 5 Year
3084 VIG.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3086 VIG.Low_Log Log of
3087 VIG.Low_mva200 200 Day MA
3093 VIG.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3095 VIG.Close_Log Log of
3096 VIG.Close_mva200 200 Day MA
3111 VIG.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3113 VIG.Adjusted_Log Log of
3114 VIG.Adjusted_mva200 200 Day MA
3117 WLRRAL_YoY4 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) 4 Year over 4 Year
3119 WLRRAL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA)
3121 WLRRAL_SmoothDer Derivative of Smoothed Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA)
3123 WLRRAL_mva200 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) 200 Day MA
3124 WLRRAL_mva050 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) 50 Day MA
3130 FEDFUNDS_SmoothDer Derivative of Smoothed Effective Federal Funds Rate
3132 FEDFUNDS_mva200 Effective Federal Funds Rate 200 Day MA
3139 GPDI_SmoothDer Derivative of Smoothed Gross Private Domestic Investment
3140 GPDI_Log Log of Gross Private Domestic Investment
3141 GPDI_mva200 Gross Private Domestic Investment 200 Day MA
3142 GPDI_mva050 Gross Private Domestic Investment 50 Day MA
3148 W790RC1Q027SBEA_SmoothDer Derivative of Smoothed Net domestic investment: Private: Domestic busines
3149 W790RC1Q027SBEA_Log Log of Net domestic investment: Private: Domestic busines
3150 W790RC1Q027SBEA_mva200 Net domestic investment: Private: Domestic busines 200 Day MA
3151 W790RC1Q027SBEA_mva050 Net domestic investment: Private: Domestic busines 50 Day MA
3158 MZMV_Log Log of Velocity of MZM Money Stock
3159 MZMV_mva200 Velocity of MZM Money Stock 200 Day MA
3160 MZMV_mva050 Velocity of MZM Money Stock 50 Day MA
3164 M1_Smooth Savitsky-Golay Smoothed (p=3, n=365) M1 Money Stock
3167 M1_Log Log of M1 Money Stock
3169 M1_mva050 M1 Money Stock 50 Day MA
3173 M2_Smooth Savitsky-Golay Smoothed (p=3, n=365) M2 Money Stock
3176 M2_Log Log of M2 Money Stock
3178 M2_mva050 M2 Money Stock 50 Day MA
3195 IPMAN_mva200 Industrial Production: Manufacturing (NAICS) 200 Day MA
3199 IWD.Open_YoY5 5 Year over 5 Year
3201 IWD.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3203 IWD.Open_Log Log of
3204 IWD.Open_mva200 200 Day MA
3210 IWD.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3212 IWD.High_Log Log of
3213 IWD.High_mva200 200 Day MA
3219 IWD.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3222 IWD.Low_mva200 200 Day MA
3228 IWD.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3231 IWD.Close_mva200 200 Day MA
3246 IWD.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
3249 IWD.Adjusted_mva200 200 Day MA
3250 IWD.Adjusted_mva050 50 Day MA
3254 GS5_Smooth Savitsky-Golay Smoothed (p=3, n=365) 5-Year Treasury Constant Maturity Rate
3257 GS5_Log Log of 5-Year Treasury Constant Maturity Rate
3258 GS5_mva200 5-Year Treasury Constant Maturity Rate 200 Day MA
3259 GS5_mva050 5-Year Treasury Constant Maturity Rate 50 Day MA
3272 VIXCLS_Smooth Savitsky-Golay Smoothed (p=3, n=365) CBOE Volatility Index
3274 VIXCLS_SmoothDer Derivative of Smoothed CBOE Volatility Index
3283 VXX.Open_SmoothDer Derivative of Smoothed
3292 VXX.High_SmoothDer Derivative of Smoothed
3301 VXX.Low_SmoothDer Derivative of Smoothed
3310 VXX.Close_SmoothDer Derivative of Smoothed
3315 VXX.Volume_YoY4 4 Year over 4 Year
3316 VXX.Volume_YoY5 5 Year over 5 Year
3317 VXX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3320 VXX.Volume_Log Log of
3321 VXX.Volume_mva200 200 Day MA
3328 VXX.Adjusted_SmoothDer Derivative of Smoothed
3337 HOUST1F_SmoothDer Derivative of Smoothed Privately Owned Housing Starts: 1-Unit Structures
3347 GFDEBTN_Log Log of Federal Debt: Total Public Debt
3348 GFDEBTN_mva200 Federal Debt: Total Public Debt 200 Day MA
3349 GFDEBTN_mva050 Federal Debt: Total Public Debt 50 Day MA
3365 MSPUS_Log Log of Median Sales Price of Houses Sold for the United States
3366 MSPUS_mva200 Median Sales Price of Houses Sold for the United States 200 Day MA
3367 MSPUS_mva050 Median Sales Price of Houses Sold for the United States 50 Day MA
3371 UMDMNO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Manufacturers’ New Orders: Durable Goods (NSA)
3373 UMDMNO_SmoothDer Derivative of Smoothed Manufacturers’ New Orders: Durable Goods (NSA)
3375 UMDMNO_mva200 Manufacturers’ New Orders: Durable Goods (NSA) 200 Day MA
3376 UMDMNO_mva050 Manufacturers’ New Orders: Durable Goods (NSA) 50 Day MA
3384 DGORDER_mva200 Manufacturers’ New Orders: Durable Goods (SA) 200 Day MA
3392 CSUSHPINSA_Log Log of S&P/Case-Shiller U.S. National Home Price Index (NSA)
3393 CSUSHPINSA_mva200 S&P/Case-Shiller U.S. National Home Price Index (NSA) 200 Day MA
3394 CSUSHPINSA_mva050 S&P/Case-Shiller U.S. National Home Price Index (NSA) 50 Day MA
3398 GFDEGDQ188S_Smooth Savitsky-Golay Smoothed (p=3, n=365) Federal Debt: Total Public Debt as Percent of Gross Domestic Product
3400 GFDEGDQ188S_SmoothDer Derivative of Smoothed Federal Debt: Total Public Debt as Percent of Gross Domestic Product
3401 GFDEGDQ188S_Log Log of Federal Debt: Total Public Debt as Percent of Gross Domestic Product
3407 FYFSD_Smooth Savitsky-Golay Smoothed (p=3, n=365) Federal Surplus or Deficit
3410 FYFSD_Log Log of Federal Surplus or Deficit
3411 FYFSD_mva200 Federal Surplus or Deficit 200 Day MA
3412 FYFSD_mva050 Federal Surplus or Deficit 50 Day MA
3413 FYFSGDA188S_YoY Federal Surplus or Deficit [-] as Percent of Gross Domestic Product Year over Year
3419 FYFSGDA188S_Log Log of Federal Surplus or Deficit [-] as Percent of Gross Domestic Product
3420 FYFSGDA188S_mva200 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 200 Day MA
3421 FYFSGDA188S_mva050 Federal Surplus or Deficit [-] as Percent of Gross Domestic Product 50 Day MA
3427 GOLDAMGBD228NLBM_SmoothDer Derivative of Smoothed Gold Fixing Price 10:30 A.M. (London time) in London Bullion Market
3470 GDX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3487 XLE.Open_YoY5 5 Year over 5 Year
3488 XLE.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3492 XLE.Open_mva200 200 Day MA
3493 XLE.Open_mva050 50 Day MA
3497 XLE.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3501 XLE.High_mva200 200 Day MA
3502 XLE.High_mva050 50 Day MA
3506 XLE.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3510 XLE.Low_mva200 200 Day MA
3511 XLE.Low_mva050 50 Day MA
3515 XLE.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3519 XLE.Close_mva200 200 Day MA
3520 XLE.Close_mva050 50 Day MA
3524 XLE.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3526 XLE.Volume_SmoothDer Derivative of Smoothed
3533 XLE.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3537 XLE.Adjusted_mva200 200 Day MA
3538 XLE.Adjusted_mva050 50 Day MA
3541 GSG.Open_YoY5 5 Year over 5 Year
3542 GSG.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3546 GSG.Open_mva200 200 Day MA
3547 GSG.Open_mva050 50 Day MA
3550 GSG.High_YoY5 5 Year over 5 Year
3551 GSG.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3555 GSG.High_mva200 200 Day MA
3556 GSG.High_mva050 50 Day MA
3560 GSG.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3564 GSG.Low_mva200 200 Day MA
3565 GSG.Low_mva050 50 Day MA
3569 GSG.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3573 GSG.Close_mva200 200 Day MA
3574 GSG.Close_mva050 50 Day MA
3578 GSG.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3582 GSG.Volume_mva200 200 Day MA
3587 GSG.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3591 GSG.Adjusted_mva200 200 Day MA
3592 GSG.Adjusted_mva050 50 Day MA
3596 WALCL_Smooth Savitsky-Golay Smoothed (p=3, n=365) All Federal Reserve Banks: Total Assets
3597 WALCL_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) All Federal Reserve Banks: Total Assets
3599 WALCL_Log Log of All Federal Reserve Banks: Total Assets
3600 WALCL_mva200 All Federal Reserve Banks: Total Assets 200 Day MA
3601 WALCL_mva050 All Federal Reserve Banks: Total Assets 50 Day MA
3604 OUTMS_YoY5 Manufacturing Sector: Real Output 5 Year over 5 Year
3608 OUTMS_Log Log of Manufacturing Sector: Real Output
3609 OUTMS_mva200 Manufacturing Sector: Real Output 200 Day MA
3610 OUTMS_mva050 Manufacturing Sector: Real Output 50 Day MA
3614 MANEMP_Smooth Savitsky-Golay Smoothed (p=3, n=365) All Employees: Manufacturing
3616 MANEMP_SmoothDer Derivative of Smoothed All Employees: Manufacturing
3617 MANEMP_Log Log of All Employees: Manufacturing
3618 MANEMP_mva200 All Employees: Manufacturing 200 Day MA
3619 MANEMP_mva050 All Employees: Manufacturing 50 Day MA
3622 PRS30006163_YoY5 Manufacturing Sector: Real Output Per Person 5 Year over 5 Year
3626 PRS30006163_Log Log of Manufacturing Sector: Real Output Per Person
3627 PRS30006163_mva200 Manufacturing Sector: Real Output Per Person 200 Day MA
3628 PRS30006163_mva050 Manufacturing Sector: Real Output Per Person 50 Day MA
3634 BAMLC0A3CA_SmoothDer Derivative of Smoothed ICE BofAML US Corporate A Option-Adjusted Spread
3648 SOFR_YoY4 Secured Overnight Financing Rate 4 Year over 4 Year
3649 SOFR_YoY5 Secured Overnight Financing Rate 5 Year over 5 Year
3650 SOFR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate
3652 SOFR_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate
3653 SOFR_Log Log of Secured Overnight Financing Rate
3659 SOFRVOL_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Volume
3661 SOFRVOL_SmoothDer Derivative of Smoothed Secured Overnight Financing Volume
3666 SOFR99_YoY4 Secured Overnight Financing Rate: 99th Percentile 4 Year over 4 Year
3667 SOFR99_YoY5 Secured Overnight Financing Rate: 99th Percentile 5 Year over 5 Year
3671 SOFR99_Log Log of Secured Overnight Financing Rate: 99th Percentile
3673 SOFR99_mva050 Secured Overnight Financing Rate: 99th Percentile 50 Day MA
3677 SOFR75_Smooth Savitsky-Golay Smoothed (p=3, n=365) Secured Overnight Financing Rate: 75th Percentile
3679 SOFR75_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 75th Percentile
3688 SOFR25_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 25th Percentile
3689 SOFR25_Log Log of Secured Overnight Financing Rate: 25th Percentile
3697 SOFR1_SmoothDer Derivative of Smoothed Secured Overnight Financing Rate: 1st Percentile
3698 SOFR1_Log Log of Secured Overnight Financing Rate: 1st Percentile
3704 OBFR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate
3706 OBFR_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate
3713 OBFR99_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 99th Percentile
3715 OBFR99_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 99th Percentile
3724 OBFR75_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 75th Percentile
3731 OBFR25_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 25th Percentile
3733 OBFR25_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 25th Percentile
3740 OBFR1_Smooth Savitsky-Golay Smoothed (p=3, n=365) Overnight Bank Funding Rate: 1st Percentile
3741 OBFR1_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Overnight Bank Funding Rate: 1st Percentile
3742 OBFR1_SmoothDer Derivative of Smoothed Overnight Bank Funding Rate: 1st Percentile
3743 OBFR1_Log Log of Overnight Bank Funding Rate: 1st Percentile
3744 OBFR1_mva200 Overnight Bank Funding Rate: 1st Percentile 200 Day MA
3752 RPONTSYD_Log Log of Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations
3753 RPONTSYD_mva200 Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations 200 Day MA
3755 IOER_YoY Interest Rate on Excess Reserves Year over Year
3756 IOER_YoY4 Interest Rate on Excess Reserves 4 Year over 4 Year
3757 IOER_YoY5 Interest Rate on Excess Reserves 5 Year over 5 Year
3760 IOER_SmoothDer Derivative of Smoothed Interest Rate on Excess Reserves
3761 IOER_Log Log of Interest Rate on Excess Reserves
3762 IOER_mva200 Interest Rate on Excess Reserves 200 Day MA
3763 IOER_mva050 Interest Rate on Excess Reserves 50 Day MA
3771 WRESBAL_mva200 Reserve Balances with Federal Reserve Banks 200 Day MA
3778 EXCSRESNW_SmoothDer Derivative of Smoothed Excess Reserves of Depository Institutions
3779 EXCSRESNW_Log Log of Excess Reserves of Depository Institutions
3780 EXCSRESNW_mva200 Excess Reserves of Depository Institutions 200 Day MA
3781 EXCSRESNW_mva050 Excess Reserves of Depository Institutions 50 Day MA
3782 ECBASSETS_YoY Central Bank Assets for Euro Area (11-19 Countries) Year over Year
3788 ECBASSETS_Log Log of Central Bank Assets for Euro Area (11-19 Countries)
3789 ECBASSETS_mva200 Central Bank Assets for Euro Area (11-19 Countries) 200 Day MA
3790 ECBASSETS_mva050 Central Bank Assets for Euro Area (11-19 Countries) 50 Day MA
3797 EUNNGDP_Log Log of Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries)
3798 EUNNGDP_mva200 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 200 Day MA
3799 EUNNGDP_mva050 Gross Domestic Product (Euro/ECU series) for Euro Area (19 Countries) 50 Day MA
3814 USD1MTD156N_SmoothDer Derivative of Smoothed 1-Month London Interbank Offered Rate (LIBOR), based on U.S. Dollar
3821 CURRENCY_Smooth Savitsky-Golay Smoothed (p=3, n=365) Currency Component of M1 (Seasonally Adjusted)
3824 CURRENCY_Log Log of Currency Component of M1 (Seasonally Adjusted)
3825 CURRENCY_mva200 Currency Component of M1 (Seasonally Adjusted) 200 Day MA
3826 CURRENCY_mva050 Currency Component of M1 (Seasonally Adjusted) 50 Day MA
3833 WCURRNS_Log Log of Currency Component of M1
3834 WCURRNS_mva200 Currency Component of M1 200 Day MA
3835 WCURRNS_mva050 Currency Component of M1 50 Day MA
3842 BOGMBASE_Log Log of Monetary Base; Total
3843 BOGMBASE_mva200 Monetary Base; Total 200 Day MA
3844 BOGMBASE_mva050 Monetary Base; Total 50 Day MA
3851 PRS88003193_Log Log of Nonfinancial Corporations Sector: Unit Profits
3852 PRS88003193_mva200 Nonfinancial Corporations Sector: Unit Profits 200 Day MA
3853 PRS88003193_mva050 Nonfinancial Corporations Sector: Unit Profits 50 Day MA
3860 PPIACO_Log Log of Producer Price Index for All Commodities
3861 PPIACO_mva200 Producer Price Index for All Commodities 200 Day MA
3862 PPIACO_mva050 Producer Price Index for All Commodities 50 Day MA
3869 PCUOMFGOMFG_Log Log of Producer Price Index by Industry: Total Manufacturing Industries
3870 PCUOMFGOMFG_mva200 Producer Price Index by Industry: Total Manufacturing Industries 200 Day MA
3871 PCUOMFGOMFG_mva050 Producer Price Index by Industry: Total Manufacturing Industries 50 Day MA
3878 POPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Population (U.S.)
3879 POPTHM_Smooth Savitsky-Golay Smoothed (p=3, n=365) Population (U.S.)
3882 POPTHM_SmoothDer Derivative of Smoothed Population (U.S.)
3883 POPTHM_SmoothDer Derivative of Smoothed Population (U.S.)
3884 POPTHM_Log Log of Population (U.S.)
3885 POPTHM_Log Log of Population (U.S.)
3886 POPTHM_mva200 Population (U.S.) 200 Day MA
3887 POPTHM_mva200 Population (U.S.) 200 Day MA
3888 POPTHM_mva050 Population (U.S.) 50 Day MA
3889 POPTHM_mva050 Population (U.S.) 50 Day MA
3896 POPTHM.1_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3897 POPTHM.1_Smooth Savitsky-Golay Smoothed (p=3, n=365)
3900 POPTHM.1_SmoothDer Derivative of Smoothed
3901 POPTHM.1_SmoothDer Derivative of Smoothed
3902 POPTHM.1_Log Log of
3903 POPTHM.1_Log Log of
3904 POPTHM.1_mva200 200 Day MA
3905 POPTHM.1_mva200 200 Day MA
3906 POPTHM.1_mva050 50 Day MA
3907 POPTHM.1_mva050 50 Day MA
3915 CLF16OV_mva200 Civilian Labor Force Level, SA 200 Day MA
3918 LNU01000000_YoY4 Civilian Labor Force Level, NSA 4 Year over 4 Year
3924 LNU01000000_mva200 Civilian Labor Force Level, NSA 200 Day MA
3950 RSAFS_Log Log of Advance Retail Sales: Retail and Food Services
3952 RSAFS_mva050 Advance Retail Sales: Retail and Food Services 50 Day MA
3968 BOPGTB_Log Log of Trade Balance: Goods, Balance of Payments Basis (SA)
3976 TERMCBPER24NS_SmoothDer Derivative of Smoothed Finance Rate on Personal Loans at Commercial Banks, 24 Month Loan
3980 A065RC1A027NBEA_YoY Personal income (NSA) Year over Year
3986 A065RC1A027NBEA_Log Log of Personal income (NSA)
3987 A065RC1A027NBEA_mva200 Personal income (NSA) 200 Day MA
3988 A065RC1A027NBEA_mva050 Personal income (NSA) 50 Day MA
4004 PCE_Log Log of Personal Consumption Expenditures (SA)
4005 PCE_mva200 Personal Consumption Expenditures (SA) 200 Day MA
4006 PCE_mva050 Personal Consumption Expenditures (SA) 50 Day MA
4013 A053RC1Q027SBEA_Log Log of National income: Corporate profits before tax (without IVA and CCAdj)
4014 A053RC1Q027SBEA_mva200 National income: Corporate profits before tax (without IVA and CCAdj) 200 Day MA
4015 A053RC1Q027SBEA_mva050 National income: Corporate profits before tax (without IVA and CCAdj) 50 Day MA
4022 CPROFIT_Log Log of Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj)
4023 CPROFIT_mva200 Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 200 Day MA
4024 CPROFIT_mva050 Corporate Profits with Inventory Valuation Adjustment (IVA) and Capital Consumption Adjustment (CCAdj) 50 Day MA
4027 SPY.Open_YoY5 5 Year over 5 Year
4028 SPY.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4029 SPY.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4031 SPY.Open_Log Log of
4032 SPY.Open_mva200 200 Day MA
4037 SPY.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4038 SPY.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4040 SPY.High_Log Log of
4041 SPY.High_mva200 200 Day MA
4045 SPY.Low_YoY5 5 Year over 5 Year
4047 SPY.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4049 SPY.Low_Log Log of
4050 SPY.Low_mva200 200 Day MA
4055 SPY.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4056 SPY.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4058 SPY.Close_Log Log of
4059 SPY.Close_mva200 200 Day MA
4064 SPY.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4073 SPY.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4074 SPY.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4076 SPY.Adjusted_Log Log of
4077 SPY.Adjusted_mva200 200 Day MA
4081 MDY.Open_YoY5 5 Year over 5 Year
4082 MDY.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4083 MDY.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4085 MDY.Open_Log Log of
4086 MDY.Open_mva200 200 Day MA
4091 MDY.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4092 MDY.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4094 MDY.High_Log Log of
4095 MDY.High_mva200 200 Day MA
4096 MDY.High_mva050 50 Day MA
4099 MDY.Low_YoY5 5 Year over 5 Year
4100 MDY.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4101 MDY.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4103 MDY.Low_Log Log of
4104 MDY.Low_mva200 200 Day MA
4105 MDY.Low_mva050 50 Day MA
4109 MDY.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4110 MDY.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4113 MDY.Close_mva200 200 Day MA
4114 MDY.Close_mva050 50 Day MA
4118 MDY.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4127 MDY.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4128 MDY.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4131 MDY.Adjusted_mva200 200 Day MA
4132 MDY.Adjusted_mva050 50 Day MA
4136 EES.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4137 EES.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4139 EES.Open_Log Log of
4140 EES.Open_mva200 200 Day MA
4145 EES.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4146 EES.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4148 EES.High_Log Log of
4149 EES.High_mva200 200 Day MA
4154 EES.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4155 EES.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4157 EES.Low_Log Log of
4158 EES.Low_mva200 200 Day MA
4163 EES.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4164 EES.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4167 EES.Close_mva200 200 Day MA
4175 EES.Volume_Log Log of
4181 EES.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4182 EES.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4185 EES.Adjusted_mva200 200 Day MA
4190 IJR.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4191 IJR.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4193 IJR.Open_Log Log of
4194 IJR.Open_mva200 200 Day MA
4199 IJR.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4200 IJR.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4202 IJR.High_Log Log of
4203 IJR.High_mva200 200 Day MA
4208 IJR.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4209 IJR.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4211 IJR.Low_Log Log of
4212 IJR.Low_mva200 200 Day MA
4217 IJR.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4218 IJR.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4221 IJR.Close_mva200 200 Day MA
4235 IJR.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4236 IJR.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4239 IJR.Adjusted_mva200 200 Day MA
4245 VGSTX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4247 VGSTX.Open_Log Log of
4248 VGSTX.Open_mva200 200 Day MA
4254 VGSTX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4256 VGSTX.High_Log Log of
4257 VGSTX.High_mva200 200 Day MA
4263 VGSTX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4265 VGSTX.Low_Log Log of
4266 VGSTX.Low_mva200 200 Day MA
4272 VGSTX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4274 VGSTX.Close_Log Log of
4275 VGSTX.Close_mva200 200 Day MA
4277 VGSTX.Volume_YoY Year over Year
4278 VGSTX.Volume_YoY4 4 Year over 4 Year
4279 VGSTX.Volume_YoY5 5 Year over 5 Year
4280 VGSTX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4281 VGSTX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4282 VGSTX.Volume_SmoothDer Derivative of Smoothed
4283 VGSTX.Volume_Log Log of
4284 VGSTX.Volume_mva200 200 Day MA
4285 VGSTX.Volume_mva050 50 Day MA
4289 VGSTX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4290 VGSTX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4292 VGSTX.Adjusted_Log Log of
4293 VGSTX.Adjusted_mva200 200 Day MA
4298 VFINX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4299 VFINX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4301 VFINX.Open_Log Log of
4302 VFINX.Open_mva200 200 Day MA
4307 VFINX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4308 VFINX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4310 VFINX.High_Log Log of
4311 VFINX.High_mva200 200 Day MA
4316 VFINX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4317 VFINX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4319 VFINX.Low_Log Log of
4320 VFINX.Low_mva200 200 Day MA
4325 VFINX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4326 VFINX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4328 VFINX.Close_Log Log of
4329 VFINX.Close_mva200 200 Day MA
4331 VFINX.Volume_YoY Year over Year
4332 VFINX.Volume_YoY4 4 Year over 4 Year
4333 VFINX.Volume_YoY5 5 Year over 5 Year
4334 VFINX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4335 VFINX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4336 VFINX.Volume_SmoothDer Derivative of Smoothed
4337 VFINX.Volume_Log Log of
4338 VFINX.Volume_mva200 200 Day MA
4339 VFINX.Volume_mva050 50 Day MA
4343 VFINX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4344 VFINX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4346 VFINX.Adjusted_Log Log of
4347 VFINX.Adjusted_mva200 200 Day MA
4353 VOE.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4355 VOE.Open_Log Log of
4356 VOE.Open_mva200 200 Day MA
4357 VOE.Open_mva050 50 Day MA
4362 VOE.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4364 VOE.High_Log Log of
4365 VOE.High_mva200 200 Day MA
4366 VOE.High_mva050 50 Day MA
4371 VOE.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4374 VOE.Low_mva200 200 Day MA
4375 VOE.Low_mva050 50 Day MA
4380 VOE.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4383 VOE.Close_mva200 200 Day MA
4384 VOE.Close_mva050 50 Day MA
4398 VOE.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4401 VOE.Adjusted_mva200 200 Day MA
4402 VOE.Adjusted_mva050 50 Day MA
4406 VOT.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4407 VOT.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4408 VOT.Open_SmoothDer Derivative of Smoothed
4409 VOT.Open_Log Log of
4410 VOT.Open_mva200 200 Day MA
4411 VOT.Open_mva050 50 Day MA
4414 VOT.High_YoY5 5 Year over 5 Year
4415 VOT.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4416 VOT.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4417 VOT.High_SmoothDer Derivative of Smoothed
4418 VOT.High_Log Log of
4419 VOT.High_mva200 200 Day MA
4420 VOT.High_mva050 50 Day MA
4423 VOT.Low_YoY5 5 Year over 5 Year
4424 VOT.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4425 VOT.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4426 VOT.Low_SmoothDer Derivative of Smoothed
4427 VOT.Low_Log Log of
4428 VOT.Low_mva200 200 Day MA
4429 VOT.Low_mva050 50 Day MA
4433 VOT.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4434 VOT.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4435 VOT.Close_SmoothDer Derivative of Smoothed
4436 VOT.Close_Log Log of
4437 VOT.Close_mva200 200 Day MA
4438 VOT.Close_mva050 50 Day MA
4444 VOT.Volume_SmoothDer Derivative of Smoothed
4451 VOT.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4452 VOT.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4453 VOT.Adjusted_SmoothDer Derivative of Smoothed
4454 VOT.Adjusted_Log Log of
4455 VOT.Adjusted_mva200 200 Day MA
4456 VOT.Adjusted_mva050 50 Day MA
4460 TMFGX.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4461 TMFGX.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4462 TMFGX.Open_SmoothDer Derivative of Smoothed
4464 TMFGX.Open_mva200 200 Day MA
4465 TMFGX.Open_mva050 50 Day MA
4469 TMFGX.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4470 TMFGX.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4471 TMFGX.High_SmoothDer Derivative of Smoothed
4473 TMFGX.High_mva200 200 Day MA
4474 TMFGX.High_mva050 50 Day MA
4478 TMFGX.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4479 TMFGX.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4480 TMFGX.Low_SmoothDer Derivative of Smoothed
4482 TMFGX.Low_mva200 200 Day MA
4483 TMFGX.Low_mva050 50 Day MA
4487 TMFGX.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4488 TMFGX.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4489 TMFGX.Close_SmoothDer Derivative of Smoothed
4491 TMFGX.Close_mva200 200 Day MA
4492 TMFGX.Close_mva050 50 Day MA
4493 TMFGX.Volume_YoY Year over Year
4494 TMFGX.Volume_YoY4 4 Year over 4 Year
4495 TMFGX.Volume_YoY5 5 Year over 5 Year
4496 TMFGX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4497 TMFGX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4498 TMFGX.Volume_SmoothDer Derivative of Smoothed
4499 TMFGX.Volume_Log Log of
4500 TMFGX.Volume_mva200 200 Day MA
4501 TMFGX.Volume_mva050 50 Day MA
4505 TMFGX.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4506 TMFGX.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4507 TMFGX.Adjusted_SmoothDer Derivative of Smoothed
4509 TMFGX.Adjusted_mva200 200 Day MA
4510 TMFGX.Adjusted_mva050 50 Day MA
4514 IWM.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4515 IWM.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4517 IWM.Open_Log Log of
4518 IWM.Open_mva200 200 Day MA
4523 IWM.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4524 IWM.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4526 IWM.High_Log Log of
4527 IWM.High_mva200 200 Day MA
4532 IWM.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4533 IWM.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4535 IWM.Low_Log Log of
4536 IWM.Low_mva200 200 Day MA
4541 IWM.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4542 IWM.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4545 IWM.Close_mva200 200 Day MA
4559 IWM.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4560 IWM.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4563 IWM.Adjusted_mva200 200 Day MA
4567 ONEQ.Open_YoY5 5 Year over 5 Year
4568 ONEQ.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4569 ONEQ.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4571 ONEQ.Open_Log Log of
4572 ONEQ.Open_mva200 200 Day MA
4576 ONEQ.High_YoY5 5 Year over 5 Year
4577 ONEQ.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4578 ONEQ.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4580 ONEQ.High_Log Log of
4581 ONEQ.High_mva200 200 Day MA
4586 ONEQ.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4587 ONEQ.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4589 ONEQ.Low_Log Log of
4590 ONEQ.Low_mva200 200 Day MA
4595 ONEQ.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4596 ONEQ.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4598 ONEQ.Close_Log Log of
4599 ONEQ.Close_mva200 200 Day MA
4606 ONEQ.Volume_SmoothDer Derivative of Smoothed
4613 ONEQ.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4614 ONEQ.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4616 ONEQ.Adjusted_Log Log of
4617 ONEQ.Adjusted_mva200 200 Day MA
4626 HAINX.Open_mva200 200 Day MA
4635 HAINX.High_mva200 200 Day MA
4644 HAINX.Low_mva200 200 Day MA
4653 HAINX.Close_mva200 200 Day MA
4655 HAINX.Volume_YoY Year over Year
4656 HAINX.Volume_YoY4 4 Year over 4 Year
4657 HAINX.Volume_YoY5 5 Year over 5 Year
4658 HAINX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4659 HAINX.Volume_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4660 HAINX.Volume_SmoothDer Derivative of Smoothed
4661 HAINX.Volume_Log Log of
4662 HAINX.Volume_mva200 200 Day MA
4663 HAINX.Volume_mva050 50 Day MA
4671 HAINX.Adjusted_mva200 200 Day MA
4680 VEU.Open_mva200 200 Day MA
4689 VEU.High_mva200 200 Day MA
4698 VEU.Low_mva200 200 Day MA
4707 VEU.Close_mva200 200 Day MA
4712 VEU.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4725 VEU.Adjusted_mva200 200 Day MA
4732 BIL.Open_SmoothDer Derivative of Smoothed
4741 BIL.High_SmoothDer Derivative of Smoothed
4759 BIL.Close_SmoothDer Derivative of Smoothed
4768 BIL.Volume_SmoothDer Derivative of Smoothed
4783 IVOO.Open_YoY5 5 Year over 5 Year
4784 IVOO.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4785 IVOO.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4787 IVOO.Open_Log Log of
4788 IVOO.Open_mva200 200 Day MA
4793 IVOO.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4794 IVOO.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4796 IVOO.High_Log Log of
4797 IVOO.High_mva200 200 Day MA
4798 IVOO.High_mva050 50 Day MA
4801 IVOO.Low_YoY5 5 Year over 5 Year
4802 IVOO.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4803 IVOO.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4805 IVOO.Low_Log Log of
4806 IVOO.Low_mva200 200 Day MA
4807 IVOO.Low_mva050 50 Day MA
4811 IVOO.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4812 IVOO.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4815 IVOO.Close_mva200 200 Day MA
4816 IVOO.Close_mva050 50 Day MA
4822 IVOO.Volume_SmoothDer Derivative of Smoothed
4823 IVOO.Volume_Log Log of
4829 IVOO.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4830 IVOO.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4833 IVOO.Adjusted_mva200 200 Day MA
4834 IVOO.Adjusted_mva050 50 Day MA
4837 VO.Open_YoY5 5 Year over 5 Year
4838 VO.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4839 VO.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4841 VO.Open_Log Log of
4842 VO.Open_mva200 200 Day MA
4843 VO.Open_mva050 50 Day MA
4846 VO.High_YoY5 5 Year over 5 Year
4847 VO.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4848 VO.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4850 VO.High_Log Log of
4851 VO.High_mva200 200 Day MA
4852 VO.High_mva050 50 Day MA
4855 VO.Low_YoY5 5 Year over 5 Year
4856 VO.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4857 VO.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4859 VO.Low_Log Log of
4860 VO.Low_mva200 200 Day MA
4861 VO.Low_mva050 50 Day MA
4865 VO.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4866 VO.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4868 VO.Close_Log Log of
4869 VO.Close_mva200 200 Day MA
4870 VO.Close_mva050 50 Day MA
4874 VO.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4876 VO.Volume_SmoothDer Derivative of Smoothed
4877 VO.Volume_Log Log of
4883 VO.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
4884 VO.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4886 VO.Adjusted_Log Log of
4887 VO.Adjusted_mva200 200 Day MA
4888 VO.Adjusted_mva050 50 Day MA
4893 CZA.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4895 CZA.Open_Log Log of
4896 CZA.Open_mva200 200 Day MA
4902 CZA.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4905 CZA.High_mva200 200 Day MA
4911 CZA.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4914 CZA.Low_mva200 200 Day MA
4920 CZA.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4923 CZA.Close_mva200 200 Day MA
4930 CZA.Volume_SmoothDer Derivative of Smoothed
4931 CZA.Volume_Log Log of
4938 CZA.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4941 CZA.Adjusted_mva200 200 Day MA
4947 VYM.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4949 VYM.Open_Log Log of
4950 VYM.Open_mva200 200 Day MA
4956 VYM.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4958 VYM.High_Log Log of
4959 VYM.High_mva200 200 Day MA
4965 VYM.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4967 VYM.Low_Log Log of
4968 VYM.Low_mva200 200 Day MA
4974 VYM.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4977 VYM.Close_mva200 200 Day MA
4992 VYM.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
4995 VYM.Adjusted_mva200 200 Day MA
4996 VYM.Adjusted_mva050 50 Day MA
5000 ACWI.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5001 ACWI.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5003 ACWI.Open_Log Log of
5004 ACWI.Open_mva200 200 Day MA
5009 ACWI.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5010 ACWI.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5012 ACWI.High_Log Log of
5013 ACWI.High_mva200 200 Day MA
5018 ACWI.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5019 ACWI.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5021 ACWI.Low_Log Log of
5022 ACWI.Low_mva200 200 Day MA
5027 ACWI.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5028 ACWI.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5030 ACWI.Close_Log Log of
5031 ACWI.Close_mva200 200 Day MA
5038 ACWI.Volume_SmoothDer Derivative of Smoothed
5045 ACWI.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5046 ACWI.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5048 ACWI.Adjusted_Log Log of
5049 ACWI.Adjusted_mva200 200 Day MA
5054 SLY.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5055 SLY.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5057 SLY.Open_Log Log of
5058 SLY.Open_mva200 200 Day MA
5063 SLY.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5064 SLY.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5066 SLY.High_Log Log of
5067 SLY.High_mva200 200 Day MA
5072 SLY.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5073 SLY.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5075 SLY.Low_Log Log of
5076 SLY.Low_mva200 200 Day MA
5081 SLY.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5082 SLY.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5085 SLY.Close_mva200 200 Day MA
5093 SLY.Volume_Log Log of
5099 SLY.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5100 SLY.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5103 SLY.Adjusted_mva200 200 Day MA
5107 QQQ.Open_YoY5 5 Year over 5 Year
5108 QQQ.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5109 QQQ.Open_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5110 QQQ.Open_SmoothDer Derivative of Smoothed
5111 QQQ.Open_Log Log of
5112 QQQ.Open_mva200 200 Day MA
5116 QQQ.High_YoY5 5 Year over 5 Year
5117 QQQ.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5118 QQQ.High_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5119 QQQ.High_SmoothDer Derivative of Smoothed
5120 QQQ.High_Log Log of
5121 QQQ.High_mva200 200 Day MA
5125 QQQ.Low_YoY5 5 Year over 5 Year
5126 QQQ.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5127 QQQ.Low_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5128 QQQ.Low_SmoothDer Derivative of Smoothed
5129 QQQ.Low_Log Log of
5130 QQQ.Low_mva200 200 Day MA
5134 QQQ.Close_YoY5 5 Year over 5 Year
5135 QQQ.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5136 QQQ.Close_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5137 QQQ.Close_SmoothDer Derivative of Smoothed
5138 QQQ.Close_Log Log of
5139 QQQ.Close_mva200 200 Day MA
5146 QQQ.Volume_SmoothDer Derivative of Smoothed
5152 QQQ.Adjusted_YoY5 5 Year over 5 Year
5153 QQQ.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5154 QQQ.Adjusted_Smooth.short Savitsky-Golay Smoothed (p=3, n=15)
5155 QQQ.Adjusted_SmoothDer Derivative of Smoothed
5156 QQQ.Adjusted_Log Log of
5157 QQQ.Adjusted_mva200 200 Day MA
5198 HYMB.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5200 HYMB.Volume_SmoothDer Derivative of Smoothed
5201 HYMB.Volume_Log Log of
5202 HYMB.Volume_mva200 200 Day MA
5203 HYMB.Volume_mva050 50 Day MA
5211 HYMB.Adjusted_mva200 200 Day MA
5218 GOLD.Open_SmoothDer Derivative of Smoothed
5219 GOLD.Open_Log Log of
5227 GOLD.High_SmoothDer Derivative of Smoothed
5236 GOLD.Low_SmoothDer Derivative of Smoothed
5245 GOLD.Close_SmoothDer Derivative of Smoothed
5252 GOLD.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5254 GOLD.Volume_SmoothDer Derivative of Smoothed
5255 GOLD.Volume_Log Log of
5263 GOLD.Adjusted_SmoothDer Derivative of Smoothed
5270 BKR.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5273 BKR.Open_Log Log of
5274 BKR.Open_mva200 200 Day MA
5275 BKR.Open_mva050 50 Day MA
5279 BKR.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5283 BKR.High_mva200 200 Day MA
5284 BKR.High_mva050 50 Day MA
5288 BKR.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5292 BKR.Low_mva200 200 Day MA
5293 BKR.Low_mva050 50 Day MA
5297 BKR.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5301 BKR.Close_mva200 200 Day MA
5306 BKR.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5308 BKR.Volume_SmoothDer Derivative of Smoothed
5309 BKR.Volume_Log Log of
5315 BKR.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5319 BKR.Adjusted_mva200 200 Day MA
5324 SLB.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5328 SLB.Open_mva200 200 Day MA
5333 SLB.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5337 SLB.High_mva200 200 Day MA
5342 SLB.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5346 SLB.Low_mva200 200 Day MA
5351 SLB.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5355 SLB.Close_mva200 200 Day MA
5362 SLB.Volume_SmoothDer Derivative of Smoothed
5369 SLB.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5373 SLB.Adjusted_mva200 200 Day MA
5378 HAL.Open_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5381 HAL.Open_Log Log of
5382 HAL.Open_mva200 200 Day MA
5383 HAL.Open_mva050 50 Day MA
5387 HAL.High_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5391 HAL.High_mva200 200 Day MA
5392 HAL.High_mva050 50 Day MA
5396 HAL.Low_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5400 HAL.Low_mva200 200 Day MA
5401 HAL.Low_mva050 50 Day MA
5405 HAL.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5409 HAL.Close_mva200 200 Day MA
5410 HAL.Close_mva050 50 Day MA
5414 HAL.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5416 HAL.Volume_SmoothDer Derivative of Smoothed
5417 HAL.Volume_Log Log of
5419 HAL.Volume_mva050 50 Day MA
5423 HAL.Adjusted_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5427 HAL.Adjusted_mva200 200 Day MA
5428 HAL.Adjusted_mva050 50 Day MA
5435 IP.Open_Log Log of
5468 IP.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5470 IP.Volume_SmoothDer Derivative of Smoothed
5522 PKG.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5524 PKG.Volume_SmoothDer Derivative of Smoothed
5544 UPS.Open_mva200 200 Day MA
5553 UPS.High_mva200 200 Day MA
5562 UPS.Low_mva200 200 Day MA
5571 UPS.Close_mva200 200 Day MA
5589 UPS.Adjusted_mva200 200 Day MA
5630 FDX.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5632 FDX.Volume_SmoothDer Derivative of Smoothed
5651 T.Open_Log Log of
5684 T.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5686 T.Volume_SmoothDer Derivative of Smoothed
5704 VZ.Open_SmoothDer Derivative of Smoothed
5713 VZ.High_SmoothDer Derivative of Smoothed
5722 VZ.Low_SmoothDer Derivative of Smoothed
5731 VZ.Close_SmoothDer Derivative of Smoothed
5738 VZ.Volume_Smooth Savitsky-Golay Smoothed (p=3, n=365)
5740 VZ.Volume_SmoothDer Derivative of Smoothed
5749 VZ.Adjusted_SmoothDer Derivative of Smoothed
5756 ISMMANPMI_Smooth Savitsky-Golay Smoothed (p=3, n=365) Institute of Supply Managment PMI Composite Index
5758 ISMMANPMI_SmoothDer Derivative of Smoothed Institute of Supply Managment PMI Composite Index
5767 MULTPLSP500PERATIOMONTH_SmoothDer Derivative of Smoothed S&P 500 TTM P/E
5771 MULTPLSP500SALESQUARTER_YoY S&P 500 TTM Sales (Not Inflation Adjusted) Year over Year
5777 MULTPLSP500SALESQUARTER_Log Log of S&P 500 TTM Sales (Not Inflation Adjusted)
5778 MULTPLSP500SALESQUARTER_mva200 S&P 500 TTM Sales (Not Inflation Adjusted) 200 Day MA
5779 MULTPLSP500SALESQUARTER_mva050 S&P 500 TTM Sales (Not Inflation Adjusted) 50 Day MA
5785 MULTPLSP500DIVYIELDMONTH_SmoothDer Derivative of Smoothed S&P 500 Dividend Yield by Month
5789 MULTPLSP500DIVMONTH_YoY S&P 500 Dividend by Month (Inflation Adjusted) Year over Year
5792 MULTPLSP500DIVMONTH_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 Dividend by Month (Inflation Adjusted)
5794 MULTPLSP500DIVMONTH_SmoothDer Derivative of Smoothed S&P 500 Dividend by Month (Inflation Adjusted)
5795 MULTPLSP500DIVMONTH_Log Log of S&P 500 Dividend by Month (Inflation Adjusted)
5805 CHRISCMEHG1_mva200 Copper Futures, Continuous Contract #1 (HG1) (Front Month) 200 Day MA
5807 WWDIWLDISAIRGOODMTK1_YoY Air transport, freight Year over Year
5813 WWDIWLDISAIRGOODMTK1_Log Log of Air transport, freight
5814 WWDIWLDISAIRGOODMTK1_mva200 Air transport, freight 200 Day MA
5815 WWDIWLDISAIRGOODMTK1_mva050 Air transport, freight 50 Day MA
5821 PETA103600001M_SmoothDer Derivative of Smoothed U.S. Total Gasoline Retail Sales by Refiners, Monthly
5830 PETA123600001M_SmoothDer Derivative of Smoothed U.S. Regular Gasoline Retail Sales by Refiners, Monthly
5834 PETA143B00001M_YoY U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly Year over Year
5835 PETA143B00001M_YoY4 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 4 Year over 4 Year
5836 PETA143B00001M_YoY5 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 5 Year over 5 Year
5840 PETA143B00001M_Log Log of U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly
5841 PETA143B00001M_mva200 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 200 Day MA
5842 PETA143B00001M_mva050 U.S. Midgrade Gasoline Retail Sales by Refiners, Monthly 50 Day MA
5848 PETA133B00001M_SmoothDer Derivative of Smoothed U.S. Premium Gasoline Bulk Sales (Volume) by Refiners, Monthly
5858 TOTALOGNRPUSM_Log Log of Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly
5859 TOTALOGNRPUSM_mva200 Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly 200 Day MA
5860 TOTALOGNRPUSM_mva050 Crude Oil and Natural Gas Rotary Rigs in Operation, Total, Monthly 50 Day MA
5867 TOTALPANRPUSM_Log Log of Crude Oil Rotary Rigs in Operation, Monthly
5868 TOTALPANRPUSM_mva200 Crude Oil Rotary Rigs in Operation, Monthly 200 Day MA
5869 TOTALPANRPUSM_mva050 Crude Oil Rotary Rigs in Operation, Monthly 50 Day MA
5877 TOTALNGNRPUSM_mva200 Natural Gas Rotary Rigs in Operation, Monthly 200 Day MA
5878 TOTALNGNRPUSM_mva050 Natural Gas Rotary Rigs in Operation, Monthly 50 Day MA
5885 BKRTotal_Log Log of Total Rig Count
5886 BKRTotal_mva200 Total Rig Count 200 Day MA
5887 BKRTotal_mva050 Total Rig Count 50 Day MA
5889 BKRGas_YoY4 Gas Rig Count 4 Year over 4 Year
5894 BKRGas_Log Log of Gas Rig Count
5895 BKRGas_mva200 Gas Rig Count 200 Day MA
5896 BKRGas_mva050 Gas Rig Count 50 Day MA
5903 BKROil_Log Log of Oil Rig Count
5904 BKROil_mva200 Oil Rig Count 200 Day MA
5905 BKROil_mva050 Oil Rig Count 50 Day MA
5906 FARMINCOME_YoY Net Farm Income Year over Year
5912 FARMINCOME_Log Log of Net Farm Income
5913 FARMINCOME_mva200 Net Farm Income 200 Day MA
5914 FARMINCOME_mva050 Net Farm Income 50 Day MA
5921 OPEARNINGSPERSHARE_Log Log of Operating Earnings per Share
5922 OPEARNINGSPERSHARE_mva200 Operating Earnings per Share 200 Day MA
5923 OPEARNINGSPERSHARE_mva050 Operating Earnings per Share 50 Day MA
5930 AREARNINGSPERSHARE_Log Log of As-Reported Earnings per Share
5931 AREARNINGSPERSHARE_mva200 As-Reported Earnings per Share 200 Day MA
5932 AREARNINGSPERSHARE_mva050 As-Reported Earnings per Share 50 Day MA
5936 CASHDIVIDENDSPERSHR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Cash Dividends per Share
5939 CASHDIVIDENDSPERSHR_Log Log of Cash Dividends per Share
5940 CASHDIVIDENDSPERSHR_mva200 Cash Dividends per Share 200 Day MA
5941 CASHDIVIDENDSPERSHR_mva050 Cash Dividends per Share 50 Day MA
5945 SALESPERSHR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Sales per Share
5947 SALESPERSHR_SmoothDer Derivative of Smoothed Sales per Share
5948 SALESPERSHR_Log Log of Sales per Share
5957 BOOKVALPERSHR_Log Log of Book value per Share
5958 BOOKVALPERSHR_mva200 Book value per Share 200 Day MA
5959 BOOKVALPERSHR_mva050 Book value per Share 50 Day MA
5963 CAPEXPERSHR_Smooth Savitsky-Golay Smoothed (p=3, n=365) Cap ex per Share
5965 CAPEXPERSHR_SmoothDer Derivative of Smoothed Cap ex per Share
5966 CAPEXPERSHR_Log Log of Cap ex per Share
5975 PRICE_Log Log of Price
5976 PRICE_mva200 Price 200 Day MA
5977 PRICE_mva050 Price 50 Day MA
5978 OPEARNINGSTTM_YoY TTM Operating Earnings Year over Year
5984 OPEARNINGSTTM_Log Log of TTM Operating Earnings
5985 OPEARNINGSTTM_mva200 TTM Operating Earnings 200 Day MA
5986 OPEARNINGSTTM_mva050 TTM Operating Earnings 50 Day MA
5987 AREARNINGSTTM_YoY TTM Reported Earnings Year over Year
5993 AREARNINGSTTM_Log Log of TTM Reported Earnings
5994 AREARNINGSTTM_mva200 TTM Reported Earnings 200 Day MA
5995 AREARNINGSTTM_mva050 TTM Reported Earnings 50 Day MA
5999 FINRAMarginDebt_Smooth Savitsky-Golay Smoothed (p=3, n=365) Margin Debt
6003 FINRAMarginDebt_mva200 Margin Debt 200 Day MA
6014 OCCEquityVolume_YoY Equity Options Volume Year over Year
6020 OCCEquityVolume_Log Log of Equity Options Volume
6021 OCCEquityVolume_mva200 Equity Options Volume 200 Day MA
6022 OCCEquityVolume_mva050 Equity Options Volume 50 Day MA
6023 OCCNonEquityVolume_YoY Non-Equity Options Volume Year over Year
6029 OCCNonEquityVolume_Log Log of Non-Equity Options Volume
6030 OCCNonEquityVolume_mva200 Non-Equity Options Volume 200 Day MA
6031 OCCNonEquityVolume_mva050 Non-Equity Options Volume 50 Day MA
6044 BUSLOANS.minus.BUSLOANSNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Montlhy) SA - NSA
6046 BUSLOANS.minus.BUSLOANSNSA_SmoothDer Derivative of Smoothed Business Loans (Montlhy) SA - NSA
6047 BUSLOANS.minus.BUSLOANSNSA_Log Log of Business Loans (Montlhy) SA - NSA
6048 BUSLOANS.minus.BUSLOANSNSA_mva200 Business Loans (Montlhy) SA - NSA 200 Day MA
6049 BUSLOANS.minus.BUSLOANSNSA_mva050 Business Loans (Montlhy) SA - NSA 50 Day MA
6053 BUSLOANS.minus.BUSLOANSNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Business Loans (Montlhy) SA - NSA divided by GDP
6055 BUSLOANS.minus.BUSLOANSNSA.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Montlhy) SA - NSA divided by GDP
6056 BUSLOANS.minus.BUSLOANSNSA.by.GDP_Log Log of Business Loans (Montlhy) SA - NSA divided by GDP
6057 BUSLOANS.minus.BUSLOANSNSA.by.GDP_mva200 Business Loans (Montlhy) SA - NSA divided by GDP 200 Day MA
6058 BUSLOANS.minus.BUSLOANSNSA.by.GDP_mva050 Business Loans (Montlhy) SA - NSA divided by GDP 50 Day MA
6059 BUSLOANS.by.GDP_YoY Business Loans Normalized by GDP Year over Year
6064 BUSLOANS.by.GDP_SmoothDer Derivative of Smoothed Business Loans Normalized by GDP
6086 BUSLOANSNSA.by.GDP_YoY Business Loans Normalized by GDP Year over Year
6095 TOTCI.by.GDP_YoY Business Loans (Weekly, SA) Normalized by GDP Year over Year
6100 TOTCI.by.GDP_SmoothDer Derivative of Smoothed Business Loans (Weekly, SA) Normalized by GDP
6104 TOTCINSA.by.GDP_YoY Business Loans (Weekly, NSA) Normalized by GDP Year over Year
6132 W875RX1.by.GDP_YoY4 Real Personal Income Normalized by GDP 4 Year over 4 Year
6136 W875RX1.by.GDP_SmoothDer Derivative of Smoothed Real Personal Income Normalized by GDP
6140 A065RC1A027NBEA.by.GDP_YoY Personal Income (NSA) Normalized by GDP Year over Year
6145 A065RC1A027NBEA.by.GDP_SmoothDer Derivative of Smoothed Personal Income (NSA) Normalized by GDP
6149 PI.by.GDP_YoY Personal Income (SA) Normalized by GDP Year over Year
6179 CONSUMERNSA.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Consumer Loans Not Seasonally Adjusted divided by GDP
6181 CONSUMERNSA.by.GDP_SmoothDer Derivative of Smoothed Consumer Loans Not Seasonally Adjusted divided by GDP
6182 CONSUMERNSA.by.GDP_Log Log of Consumer Loans Not Seasonally Adjusted divided by GDP
6184 CONSUMERNSA.by.GDP_mva050 Consumer Loans Not Seasonally Adjusted divided by GDP 50 Day MA
6185 RREACBM027NBOG.by.GDP_YoY Residental Real Estate Loans (Monthly, NSA) divided by GDP Year over Year
6186 RREACBM027NBOG.by.GDP_YoY4 Residental Real Estate Loans (Monthly, NSA) divided by GDP 4 Year over 4 Year
6187 RREACBM027NBOG.by.GDP_YoY5 Residental Real Estate Loans (Monthly, NSA) divided by GDP 5 Year over 5 Year
6188 RREACBM027NBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, NSA) divided by GDP
6190 RREACBM027NBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Monthly, NSA) divided by GDP
6191 RREACBM027NBOG.by.GDP_Log Log of Residental Real Estate Loans (Monthly, NSA) divided by GDP
6194 RREACBM027SBOG.by.GDP_YoY Residental Real Estate Loans (Monthly, SA) divided by GDP Year over Year
6195 RREACBM027SBOG.by.GDP_YoY4 Residental Real Estate Loans (Monthly, SA) divided by GDP 4 Year over 4 Year
6196 RREACBM027SBOG.by.GDP_YoY5 Residental Real Estate Loans (Monthly, SA) divided by GDP 5 Year over 5 Year
6197 RREACBM027SBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Monthly, SA) divided by GDP
6199 RREACBM027SBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Monthly, SA) divided by GDP
6203 RREACBW027SBOG.by.GDP_YoY Residental Real Estate Loans (Weekly, SA) divided by GDP Year over Year
6204 RREACBW027SBOG.by.GDP_YoY4 Residental Real Estate Loans (Weekly, SA) divided by GDP 4 Year over 4 Year
6206 RREACBW027SBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, SA) divided by GDP
6208 RREACBW027SBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Weekly, SA) divided by GDP
6215 RREACBW027NBOG.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Residental Real Estate Loans (Weekly, NSA) divided by GDP
6217 RREACBW027NBOG.by.GDP_SmoothDer Derivative of Smoothed Residental Real Estate Loans (Weekly, NSA) divided by GDP
6220 RREACBW027NBOG.by.GDP_mva050 Residental Real Estate Loans (Weekly, NSA) divided by GDP 50 Day MA
6224 UMDMNO.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Durable Goods (Monthly, NSA) divided by GDP
6226 UMDMNO.by.GDP_SmoothDer Derivative of Smoothed Durable Goods (Monthly, NSA) divided by GDP
6228 UMDMNO.by.GDP_mva200 Durable Goods (Monthly, NSA) divided by GDP 200 Day MA
6229 UMDMNO.by.GDP_mva050 Durable Goods (Monthly, NSA) divided by GDP 50 Day MA
6233 DGORDER.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Durable Goods (Monthly, NSA) divided by GDP
6235 DGORDER.by.GDP_SmoothDer Derivative of Smoothed Durable Goods (Monthly, NSA) divided by GDP
6237 DGORDER.by.GDP_mva200 Durable Goods (Monthly, NSA) divided by GDP 200 Day MA
6239 ASHMA.by.GDP_YoY Home Mortgages (Quarterly, NSA) divided by GDP Year over Year
6240 ASHMA.by.GDP_YoY4 Home Mortgages (Quarterly, NSA) divided by GDP 4 Year over 4 Year
6244 ASHMA.by.GDP_SmoothDer Derivative of Smoothed Home Mortgages (Quarterly, NSA) divided by GDP
6251 ASHMA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Home Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6260 ASHMA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365)
6271 CONSUMERNSA.INTEREST_SmoothDer Derivative of Smoothed Consumer Loans (Not Seasonally Adjusted) Interest Burdens
6272 CONSUMERNSA.INTEREST_Log Log of Consumer Loans (Not Seasonally Adjusted) Interest Burdens
6273 CONSUMERNSA.INTEREST_mva200 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 200 Day MA
6274 CONSUMERNSA.INTEREST_mva050 Consumer Loans (Not Seasonally Adjusted) Interest Burdens 50 Day MA
6280 CONSUMERNSA.INTEREST.by.GDP_SmoothDer Derivative of Smoothed Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
6281 CONSUMERNSA.INTEREST.by.GDP_Log Log of Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP
6283 CONSUMERNSA.INTEREST.by.GDP_mva050 Consumer Loans (Not Seasonally Adjusted) Interest Burden Divided by GDP 50 Day MA
6284 TOTLNNSA_YoY Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) Year over Year
6287 TOTLNNSA_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
6289 TOTLNNSA_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
6290 TOTLNNSA_Log Log of Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA)
6292 TOTLNNSA_mva050 Total Loans Not Seasonally Adjusted (BUSLOANS+REALLNSA+CONSUMERNSA) 50 Day MA
6293 TOTLNNSA.by.GDP_YoY Total Loans Not Seasonally Adjusted divided by GDP Year over Year
6298 TOTLNNSA.by.GDP_SmoothDer Derivative of Smoothed Total Loans Not Seasonally Adjusted divided by GDP
6305 TOTLNNSA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burdens
6314 TOTLNNSA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Total Loans Not Seasonally Adjusted Interest Burden Divided by GDP
6327 WRESBAL.by.GDP_mva200 Reserve Balances with Federal Reserve Banks Divided by GDP 200 Day MA
6334 EXCSRESNW.by.GDP_SmoothDer Derivative of Smoothed Excess Reserves of Depository Institutions Divided by GDP
6339 WLRRAL.by.GDP_YoY4 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP 4 Year over 4 Year
6341 WLRRAL.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP
6343 WLRRAL.by.GDP_SmoothDer Derivative of Smoothed Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP
6345 WLRRAL.by.GDP_mva200 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP 200 Day MA
6346 WLRRAL.by.GDP_mva050 Liabilities and Capital: Liabilities: Reverse Repurchase Agreements: Wednesday Level (NSA) Divided by GDP 50 Day MA
6358 EXPCH.minus.IMPCH_YoY5 U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis) 5 Year over 5 Year
6362 EXPCH.minus.IMPCH_Log Log of U.S. Exports to China (FAS Basis) - U.S. Imports to China (Customs Basis)
6371 EXPMX.minus.IMPMX_Log Log of
6375 SRPSABSNNCB.by.GDP_YoY4 Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP 4 Year over 4 Year
6380 SRPSABSNNCB.by.GDP_Log Log of Nonfinancial corporate business; security repurchase agreements; asset, Level (NSA) Divided by GDP
6383 ASTLL.by.GDP_YoY All sectors; total loans; liability, Level (NSA) Divided by GDP Year over Year
6388 ASTLL.by.GDP_SmoothDer Derivative of Smoothed All sectors; total loans; liability, Level (NSA) Divided by GDP
6392 ASFMA.by.GDP_YoY All sectors; farm mortgages; asset, Level (NSA) Divided by GDP Year over Year
6397 ASFMA.by.GDP_SmoothDer Derivative of Smoothed All sectors; farm mortgages; asset, Level (NSA) Divided by GDP
6404 ASFMA.by.ASTLL_Smooth Savitsky-Golay Smoothed (p=3, n=365) All sectors; total loans Divided by farm mortgages
6406 ASFMA.by.ASTLL_SmoothDer Derivative of Smoothed All sectors; total loans Divided by farm mortgages
6407 ASFMA.by.ASTLL_Log Log of All sectors; total loans Divided by farm mortgages
6413 ASFMA.INTEREST_Smooth Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) 30-Year Fixed Interest Burdens
6422 ASFMA.INTEREST.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Farm Mortgages (Quarterly, NSA) Interest Burden Divided by GDP
6428 FARMINCOME.by.GDP_YoY Farm Income (Annual, NSA) Divided by GDP Year over Year
6433 FARMINCOME.by.GDP_SmoothDer Derivative of Smoothed Farm Income (Annual, NSA) Divided by GDP
6440 BOGMBASE.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) BOGMBASE Divided by GDP
6443 BOGMBASE.by.GDP_Log Log of BOGMBASE Divided by GDP
6444 BOGMBASE.by.GDP_mva200 BOGMBASE Divided by GDP 200 Day MA
6445 BOGMBASE.by.GDP_mva050 BOGMBASE Divided by GDP 50 Day MA
6446 WALCL.by.GDP_YoY All Federal Reserve Banks: Total Assets Divided by GDP Year over Year
6447 WALCL.by.GDP_YoY4 All Federal Reserve Banks: Total Assets Divided by GDP 4 Year over 4 Year
6448 WALCL.by.GDP_YoY5 All Federal Reserve Banks: Total Assets Divided by GDP 5 Year over 5 Year
6449 WALCL.by.GDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) All Federal Reserve Banks: Total Assets Divided by GDP
6450 WALCL.by.GDP_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) All Federal Reserve Banks: Total Assets Divided by GDP
6451 WALCL.by.GDP_SmoothDer Derivative of Smoothed All Federal Reserve Banks: Total Assets Divided by GDP
6452 WALCL.by.GDP_Log Log of All Federal Reserve Banks: Total Assets Divided by GDP
6453 WALCL.by.GDP_mva200 All Federal Reserve Banks: Total Assets Divided by GDP 200 Day MA
6454 WALCL.by.GDP_mva050 All Federal Reserve Banks: Total Assets Divided by GDP 50 Day MA
6455 ECBASSETS.by.EUNNGDP_YoY Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP Year over Year
6458 ECBASSETS.by.EUNNGDP_Smooth Savitsky-Golay Smoothed (p=3, n=365) Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
6460 ECBASSETS.by.EUNNGDP_SmoothDer Derivative of Smoothed Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
6461 ECBASSETS.by.EUNNGDP_Log Log of Central Bank Assets for Euro Area (11-19 Countries) Divided by GDP
6470 DGS30TO10_Log Log of Yield Curve, 30 and 10 Year Treasury (DGS30-DGS10)
6474 DGS10TO1_YoY4 Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1) 4 Year over 4 Year
6479 DGS10TO1_Log Log of Yield Curve, 10 and 1 Year Treasury (DGS10-DGS1)
6488 DGS10TO2_Log Log of Yield Curve, 10 and 2 Year Treasury (DGS10-DGS2)
6492 DGS10TOTB3MS_YoY4 Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS) 4 Year over 4 Year
6494 DGS10TOTB3MS_Smooth Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
6497 DGS10TOTB3MS_Log Log of Yield Curve, 10 and 3 Month Treasury (DGS10-TB3MS)
6503 DGS10TODTB3_Smooth Savitsky-Golay Smoothed (p=3, n=365) Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
6506 DGS10TODTB3_Log Log of Yield Curve, 10 and 3 Month Treasury (DGS10-DTB3)
6514 DGS10ByAAA_SmoothDer Derivative of Smoothed AAA ratio to 10 year treasury (AAA/DGS10)
6542 NPPTTLBYPOPTHM_Log Log of ADP Private Employment / Population
6543 NPPTTLBYPOPTHM_mva200 ADP Private Employment / Population 200 Day MA
6544 NPPTTLBYPOPTHM_mva050 ADP Private Employment / Population 50 Day MA
6550 U6toU3_SmoothDer Derivative of Smoothed U6RATE minums UNRATE
6574 DCOILBRENTEU.by.PPIACO_YoY5 Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 5 Year over 5 Year
6575 DCOILBRENTEU.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - Brent, $/bbl, Normalized by producer price index c.o.
6579 DCOILBRENTEU.by.PPIACO_mva200 Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 200 Day MA
6580 DCOILBRENTEU.by.PPIACO_mva050 Crude Oil - Brent, $/bbl, Normalized by producer price index c.o. 50 Day MA
6584 DCOILWTICO.by.PPIACO_Smooth Savitsky-Golay Smoothed (p=3, n=365) Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
6585 DCOILWTICO.by.PPIACO_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
6587 DCOILWTICO.by.PPIACO_Log Log of Crude Oil - WTI, $/bbl, Normalized by producer price index c.o.
6588 DCOILWTICO.by.PPIACO_mva200 Crude Oil - WTI, $/bbl, Normalized by producer price index c.o. 200 Day MA
6589 DCOILWTICO.by.PPIACO_mva050 Crude Oil - WTI, $/bbl, Normalized by producer price index c.o. 50 Day MA
6595 GOLDAMGBD228NLBM.by.PPIACO_SmoothDer Derivative of Smoothed Gold, USD/Troy OUnce, Normalized by commodities producer price index
6604 GOLDAMGBD228NLBM.by.CPIAUCSL_SmoothDer Derivative of Smoothed Gold, USD/Troy OUnce, Normalized by consumer price index
6613 GOLDAMGBD228NLBM.by.GDP_SmoothDer Derivative of Smoothed Gold, USD/Troy OUnce, Normalized by GDP
6620 GSG.Close.by.GDPDEF_Smooth Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by GDP def
6624 GSG.Close.by.GDPDEF_mva200 GSCI Commodity-Indexed Trust, Normalized by GDP def 200 Day MA
6625 GSG.Close.by.GDPDEF_mva050 GSCI Commodity-Indexed Trust, Normalized by GDP def 50 Day MA
6629 GSG.Close.by.GSPC.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365) GSCI Commodity-Indexed Trust, Normalized by S&P 500
6633 GSG.Close.by.GSPC.Close_mva200 GSCI Commodity-Indexed Trust, Normalized by S&P 500 200 Day MA
6634 GSG.Close.by.GSPC.Close_mva050 GSCI Commodity-Indexed Trust, Normalized by S&P 500 50 Day MA
6642 GDPBYPOPTHM_mva200 GDP/Population 200 Day MA
6667 GSPC.CloseBYMDY.Close_SmoothDer Derivative of Smoothed GSPC by MDY
6669 GSPC.CloseBYMDY.Close_mva200 GSPC by MDY 200 Day MA
6674 QQQ.CloseBYMDY.Close_Smooth Savitsky-Golay Smoothed (p=3, n=365) QQQ by MDY
6676 QQQ.CloseBYMDY.Close_SmoothDer Derivative of Smoothed QQQ by MDY
6678 QQQ.CloseBYMDY.Close_mva200 QQQ by MDY 200 Day MA
6683 GSPC.DailySwing_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
6685 GSPC.DailySwing_SmoothDer Derivative of Smoothed S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
6686 GSPC.DailySwing_Log Log of S&P 500 (^GSPC) Daily Swing: (High - Low) / Open
6691 GSPC.Open.by.GDPDEF_YoY5 S&P 500 (^GSPC) Open divided by GDP deflator 5 Year over 5 Year
6692 GSPC.Open.by.GDPDEF_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 (^GSPC) Open divided by GDP deflator
6693 GSPC.Open.by.GDPDEF_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) S&P 500 (^GSPC) Open divided by GDP deflator
6695 GSPC.Open.by.GDPDEF_Log Log of S&P 500 (^GSPC) Open divided by GDP deflator
6696 GSPC.Open.by.GDPDEF_mva200 S&P 500 (^GSPC) Open divided by GDP deflator 200 Day MA
6701 GSPC.Close.by.GDPDEF_Smooth Savitsky-Golay Smoothed (p=3, n=365) S&P 500 (^GSPC) Close divided by GDP deflator
6702 GSPC.Close.by.GDPDEF_Smooth.short Savitsky-Golay Smoothed (p=3, n=15) S&P 500 (^GSPC) Close divided by GDP deflator
6704 GSPC.Close.by.GDPDEF_Log Log of S&P 500 (^GSPC) Close divided by GDP deflator
6705 GSPC.Close.by.GDPDEF_mva200 S&P 500 (^GSPC) Close divided by GDP deflator 200 Day MA
6714 HNFSUSNSA.minus.HSN1FNSA_mva200 Houses for sale - houses sold 200 Day MA
6723 MSPUS.times.HOUST_mva200 New privately owned units start times median price 200 Day MA
6731 MSPUS.times.HNFSUSNSA_Log Log of New privately owned 1-family units for sale times median price
6732 MSPUS.times.HNFSUSNSA_mva200 New privately owned 1-family units for sale times median price 200 Day MA
6733 MSPUS.times.HNFSUSNSA_mva050 New privately owned 1-family units for sale times median price 50 Day MA
6741 GSPC.Open_mva050_mva200_sig Sell Signal S&P 500 50 SMA - 200 SMA
6742 MULTPLSP500PERATIOMONTH_Mean S&P 500 TTM P/E Average (Excludes Values Greater Than 50)

Equities

Equity indexes normalized by GDP

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

The last two years compare favorably with the period around the late 1950’s. Need to dig into this one.

datay <- "GSPC.Close"
ylim <- c(2000, d.GSPC.max)
my.data <- plotSimilarPeriods(df.data, dfRecession, df.symbols, datay, ylim, i.window = 60)
my.data[[1]]

Look at how the different segments of the market move

datay <- "GSPC.CloseBYMDY.Close_YoY"
ylim <- c(-50, 75)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

datay <- "GSPC.CloseBYMDY.Close"
ylim <- c(0, 20)
dtStart = as.Date('1980-01-01')
plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)

S&P 500 Normalized moving average

Look at moving average relationship by dividing the S&P 500 open price by the 200 day SMA.

datay <- "GSPC.Open_mva200_Norm"
ylim <- c(50, 125)
dt.start = as.Date('2008-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Crossovers

Look at the 50 DMA versus 200 DMA, often used as a technical indicator of market direction.

datay <- "GSPC.Open_mva050_mva200"
ylim <- c(-200, 200)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

datay <- "GSPC.Open_mva050_mva200_sig "
ylim <- c(0.0, 1.0)
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStartBackTest)

S&P 500 TTM P/E

Take a look at some of the earnings trends from SilverBlatt’s sheet.

## New names:
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## * `` -> ...2
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## * `` -> ...8
## New names:
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## New names:
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## * `` -> ...6
## * ...

Take a longer look back at as-reported and operating earnings

Market prices can out-run earnings so take a look at price to earnings.

Focus on some of the more recent activity

S&P 500 Sales

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 1500)
dt.start <- as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

datay <- "MULTPLSP500SALESQUARTER"
ylim <- c(500, 1500)
dt.start = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Unit Profits

The series peaks in the middle of a bull market.

S&P 500 dividends

12-month real dividend per share inflation adjusted November, 2018 dollars. Data courtesy Standard & Poor’s and Robert Shiller.

https://www.quandl.com/data/MULTPL/SP500_DIV_MONTH-S-P-500-Dividend-by-Month

Evaluate year over year dividend growth.

Real value dividend growth.

datay <- "MULTPLSP500DIVMONTH_YoY"
ylim <- c(-40, 20)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 dividend yield (12 month dividend per share)/price. Yields following September 2018 (including the current yield) are estimated based on 12 month dividends through September 2018, as reported by S&P. Sources: Standard & Poor’s for current S&P 500 Dividend Yield. Robert Shiller and his book Irrational Exuberance for historic S&P 500 Dividend Yields.

https://www.quandl.com/data/MULTPL/SP500_DIV_YIELD_MONTH-S-P-500-Dividend-Yield-by-Month

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(0, 12)
dtStart = as.Date('1950-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

datay <- "MULTPLSP500DIVYIELDMONTH"
ylim <- c(1, 4)
dtStart = as.Date('2001-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart, b.percentile = FALSE)

S&P 500 Volume

The log of the S&P volume has some interesting patterns, but nothing that seems to help with a recession indicator.

That is one spiky data series. Not sure there is a lot to help us here.

Russell 2000

Take a look at recent activity in the small cap market.

S&P 500 to Rusell 2000

Thirty day movement

Correlation

## Warning in max.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to max;
## returning -Inf
## Warning in min.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to min;
## returning Inf

S&P 500 to MDY (Mid-cap) 2000 Correlation

datay1 <- "RLG.Open"
ylim1 <- c(0, 2500)

datay2 <- "MDY.Open"
ylim2 <- c(0, 500)

dtStart <- as.Date("1jan2003","%d%b%Y")

w <- 30
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)
## Warning in max.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to max;
## returning -Inf
## Warning in min.default(structure(numeric(0), class = "Date"),
## structure(numeric(0), class = "Date"), : no non-missing arguments to min;
## returning Inf

Dividend Stocks

This is an interesting series, they should perform better through the recessions. Unfortunately they are short lived so there is not much data so this is more of a place holder for now.

datay <- "NOBL.Open"
ylim <- c(40, 110)
dt.start <- as.Date('2014-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dt.start)

Margin and option data

NYSE Margin Debt

Taking a look at margin debt. NYXDATA stopped providing NYSE margin debt data on Dec 2017. Data is available from FINRA, but it includes more accounts than the data did for NYXdata. I stitched togeter the data sets: data after Jan 2010 include NYSE+Others, data prior is just NYSE account data scaled up to match the FINRA data.

It tends to creep up when there is a frenzy in the stock market.

datay <- "FINRAMarginDebt_Log"
ylim <- c(5, 15)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Take a close look at recent activity

Sometimes it is more helpful to view year over year growth.

More near-term trend.

Take a look at some of the correlations

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

Comparison to the Russell 2000

datay1 <- "FINRAMarginDebt_YoY"
ylim1 <- c(-100, 100)

datay2 <- "RLG.Close_YoY"
ylim2 <- c(-100, 100)

dtStart <- as.Date("1jan1995","%d%b%Y")

w <- 90
corrName <-
  calcRollingCorr(dfRecession,
                  df.data,
                  df.symbols,
                  datay1,
                  ylim1,
                  datay2,
                  ylim2,
                  w,
                  dtStart)

OCC Options Volumes

See what is happening with the options volumes for equities. (From: https://www.theocc.com/webapps/historical-volume-query)

Looks like options on non-equity co-occurs with peaks/troughs?.

Market Volatility

Take a look at some of the indications of market volatility

CBOE VIX

As markets become complacent (low VIX) and high values, peaks often occur.

Compare the VIX to some of the ETF’s out there.

There

Not much predictive in VIX, take a quick look at the smoothed derivative.

S&P Daily Swings

Daily changes in the S&P should correlate well with the VIX.

More of a correlating series than a predictor.

Employment and payrolls

Unemployment rates

Unemployment rates will probably be useful, let’s take a look at the U-3. The data is a little noisy so there is also a smoothed version plotted. There seems to be a relationship between the unemployment rate and the recessions, but it could be a lagging indicator. This will be explored a little bit more later.

Looking at the unemployment rate, the eye is drawn to the rise and fall of the data, this suggests that the derivative might be helpful as well. The figure below shows the results, using a Savitzky-Golay FIR filter. It looks like the unemployment rate peaks in the middel of the recession. That peak might be a good buy signal.

Continuing Claims

A good measure of how much unemployment is growing.

Continued claims, also referred to as insured unemployment, is the number of people who have already filed an initial claim and who have experienced a week of unemployment and then filed a continued claim to claim benefits for that week of unemployment. Continued claims data are based on the week of unemployment, not the week when the initial claim was filed

https://fred.stlouisfed.org/series/CCNSA

A good measure of how much unemployment is growing

Initial Claims

A good measure of how much unemployment is growing.

An initial claim is a claim filed by an unemployed individual after a separation from an employer. The claim requests a determination of basic eligibility for the Unemployment Insurance program.

https://fred.stlouisfed.org/series/ICSA

Unemployment rates, year-over-year

Both the headline unemployment and U-6 number changes are similar. During the upswing on the cycle it does look like the headline number falls faster than U-6

The second derivative of the unemployment rate does have zero crossings near the middle point of a recession. This would make it a helpful buy signal for the trading strategy.

Unemployment rates, similar periods

Historically the last two years of record low unemployment appear most similar to the 1971-1973 time frame. Just before inflation took off.

Unemployment rates, U-6 and headline number.

Let’s also take a look at the total unemployed, U-6. It continues to fall as the headline number stabilizes as people return to the work force. An indicator the cycle is beginning to top out.

Difference between U6 and U3 to see how close the economy is getting to full employment.

Unemployment and market bottoms

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Initial jobless claims

We will also take a look at initial jobless claims, this should start to rise just before the unemployment rate.

It looks like the jobless claim tend to peak more towards the end of the recession. It does not seem to be as strong of a sell indicator as the U-3 rate.

Jobless claims have a seasonal component to them. One way to reduce this effect is to calculate year over year growth. That helps some, the peaks seem to be more closely aligned with the middle to end of recessions.

Take a closer look at recent data

Take a look at the percentage of the population looking for work

A bit more recent trend

Unemployment Level

ADP data here. comes out before the official numbers.

Look at the year-over-year change in ADP.

ADP data divided by the population

Payrolls

Look at the BLS data on payrolls. Check the NSA series, then we will look at YoY data.

Hours worked

Sparked by an article at Mises (https://mises.org/wire/how-alexandria-ocasio-cortez-misunderstands-american-poverty), take a look at average weekly hours

The time series is pretty lumpy, plot the YoY change

A more recent look at average weekly hours of production

Industrial Production

Industrial production is also known to fall during an economic downturm, let’s take a look at some of the data from the FRED on industrual production. It does seem to peak prior to a recession so let’s smooth and look at the derivative as it might be a good indicator as well.

Industrial production over the last ten years or so

The derivative isn’t bad, but it sometimes crosses zeros well into a recession. That is less helpful as either a buy or sell indicator. A better measure might year over year (YoY) change.

The year over year change has a similar appearance. The low values at the beginning make the year over year values larger than the more recent values. Seems like it will rank low a reliable indicator.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 12)

datay2 <- "GSPC.Close_YoY"
ylim2 <- c(-100, 50)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail Sales

Retail sales, aggregate

Retail sales also change during recession. As the plot below shows, it seems to follow the trend of industrial production. It might be too strongly correlated to add much to the model. The will be examined in the correlation section.

The derivative of retail sales is a little more erratic than is was the industrial products. Looks like it might be helpful to include in the model as well.

Retail sales, aggregate year-over-year

Take a look at year-over-year changes

Retail sales and unemployment correlations

Let’s see how that looks on year over year basis. Interesting to compare to unemployment rates there appears to a correlation over the long term.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

There is some similarity. The rolling correlation shows the inverse relationship prior to a recession.

datay1 <- "RSALESAGG_YoY"
ylim1 <- c(-12.5, 7.5)

datay2 <- "UNEMPLOY_YoY"
ylim2 <- c(-30, 100)

dtStart <- as.Date("1jan1970","%d%b%Y")

w <- 180
corrName <- calcRollingCorr(dfRecession,df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Retail sales correlation and industrial production

Industrial production and retail sales look very similar so the plot below shows the 360 correlation. The corerlation does tend to fall around a recession, although 2008 was so bad that they both fell together. Not sure if it is that useful.

datay1 <- "INDPRO"
ylim1 <- c(40, 125)

datay2 <- "RSALESAGG"
ylim2 <- c(100000, 200000)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

It is interesting to see the strong correlation; however, I suspect this is due to more to the shape of the trends. How do the YoY correlations look? They are a little less correlated, probably better to use in the machine learning later.

datay1 <- "INDPRO_YoY"
ylim1 <- c(-20, 20)

datay2 <- "RSALESAGG_YoY"
ylim2 <- c(-20, 20)

dtStart <- as.Date("1jan1981","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Advance Retail Sales

This is an advanced estimate of the retail sales value.

Also take a look at year over year

Retail sales and the labor market

Income

Real Personal Income

Real Personal Income (Excluding Transfer, Annual)

During a recession real personal income falls. In the plot the peaks can be seen prior to each recession.

datay <- "W875RX1"
ylim <- c(3000, 15000)
plotSingleQuickModern(datay, ylim)

The features we are interested in are the peaks and valleys so we’ll use the derivative to get to those. Interesting, there is usually a first zero crossing before a recession and a second during or just after the recession.

Real personal income might have some seasonal variance, but it seems the year over year change tells the same story.

Price and cost measures

This section shows price and cost measures.

Two commonly used indexes are the CPI (consumer price index) and PPI (producer price index). CPI tries to show final prices paid for goods and services by urban U.S. consumers. This index includes sales tax and imports. The PPI attempts to reflect the prices paid at all stages of production, including goods and services purchases as inputs as well as goods and services purchased by consumers from retail and producer sellers. The PPI does not include imports or sales tax. The CPI reflects all rebates and financing plans wherease the PPI reflects only those rebate and financing plans provided by the producer. For example if an automotive manufacturer offers a rebate of $500 and the dealer offers an additional rebate of $500 then the PPI would reflect only the automotive manufacturer rebate, but the CPI would reflect both rebates.

Sources; https://www.bls.gov/opub/hom/pdf/cpihom.pdf and https://www.bls.gov/opub/hom/pdf/ppi-20111028.pdf.

Consumer price index

What does CPI look like?

datay <- "CPIAUCSL"
ylim <- c(0, 300)
plotSingleQuickModern(datay, ylim)

Check out the YoY growth

datay <- "CPIAUCSL_YoY"
ylim <- c(-2, 15)
plotSingleQuickModern(datay, ylim)

CPI to PPI

Suggested by Charlie, it can be helpful to look at the relationship between producer prices and consumer prices.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Producer Price Index (Commodities)

Commodities

Basket

Take a look at some trends of baskets of commodities.

This plot examines commodity performance relative to the GDP deflator

Crude oil

Look at a trend of West Texas Intermediate (WTI)

This is ticker data from yahoo

Take a look at both WTI and Brent crude.

Real price of crude using producer price index for commodities

Gold

As risks increase investors often flock to safe haven assets like gold. An up-tick in prices can indicate investor uncertainty. This can be seen in the nominal price plot around 1980 and again in 2007.

This plots out the real price of gold by two different deflators. PPI corrected price is a little higher, to be expected since CPI also includes the effects of sales tax and imports. The spike in 1980 is especially pronounced in this series.

See how nominal and real prices look year over year. From the long-term view seems like there is little difference in the three series. Although not shown, even over the near-term there is little difference in the series.

See how gold correlates with the VIX. Both gold and VIX should respond to investor axiety, but it doesn’t look like it correlates very well.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 245 rows containing non-finite values (stat_smooth).

Copper

Dr. Copper has a reputation as an indicator of economic malaise, but it does not seem to have much of a correlation with the recessions. The series below is from CME via Quandl. It has a lot of data so I am also looking at the smoothed version.

Copper is one of the commodities in the PPI so it is a bit of a proxy for how copper is doing relative to the basket of commodities.

The change in prices, year over year, do generally peak prior to a recession. The time and shape of this peak varies, but it still might be helpful. A couple of the large troughs do seem to correlate with the end of the recession. Likely this is because industrial production has also fallen.

There is some correlation between copper and the smooth recession initiator, especially at the end of the recession.

Might be easier to see correlation in a dot plot format.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 342 rows containing non-finite values (stat_smooth).

This is a legacy series from FRED. It has not been updated in a couple of years so I am assuming it will go away.

Oil Services

Amazing events in the first half of 2020, take a look at those

See how the players are doing

Federal Reserve

The federal reserve has an impact on the economy, here are some data series relating to that.

Little bit closer

datay <- "WALCL"
ylim <- c(0, 8500)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Federal Reserve Reverse Repo Agreements

Compare liabilities to reverse repo trends

Spiky, might be easier to look at year-over-year

Normalized by GDP

datay <- "WLRRAL.by.GDP"
ylim <- c(0, 4)
dtStart = as.Date('2003-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Overnight Bank Funding Rate

“The overnight bank funding rate is calculated using federal funds transactions and certain Eurodollar transactions. The federal funds market consists of domestic unsecured borrowings in U.S. dollars by depository institutions from other depository institutions and certain other entities, primarily government-sponsored enterprises, while the Eurodollar market consists of unsecured U.S. dollar deposits held at banks or bank branches outside of the United States. U.S.-based banks can also take Eurodollar deposits domestically through international banking facilities (IBFs). The overnight bank funding rate (OBFR) is calculated as a volume-weighted median of overnight federal funds transactions and Eurodollar transactions reported in the FR 2420 Report of Selected Money Market Rates. Volume-weighted median is the rate associated with transactions at the 50th percentile of transaction volume. Specifically, the volume-weighted median rate is calculated by ordering the transactions from lowest to highest rate, taking the cumulative sum of volumes of these transactions, and identifying the rate associated with the trades at the 50th percentile of dollar volume. The published rates are the volume-weighted median transacted rate, rounded to the nearest basis point.” https://www.newyorkfed.org/markets/obfrinfo.

Secured Overnight Financing Rate

“The Secured Overnight Financing Rate (SOFR) is a broad measure of the cost of borrowing cash overnight collateralized by Treasury securities. The SOFR includes all trades in the Broad General Collateral Rate plus bilateral Treasury repurchase agreement (repo) transactions cleared through the Delivery-versus-Payment (DVP) service offered by the Fixed Income Clearing Corporation (FICC), which is filtered to remove a portion of transactions considered “specials” " https://apps.newyorkfed.org/markets/autorates/sofr

Take a look at the variation (99th - 1st percentile)

Reserve Balances with Federal Reserve Banks

Hard to get a sense of these series in the absolute. Take a look relative to GDP.

By double entry book-keeping reserves+loans (assets) = deposit (liabilities). Does that really work?

Correlation Between Reserves and Total Loans

As reserves increase there should be less lending. That correlation generally holds.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Did the reserve balances increase after the 2016 and 2018 drops? Not in the same way. There are some relationships between the equities market and the reserves though.

Explicitly correlate reserve balances and total loans. It is a weak and noisy correlation.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 990 rows containing non-finite values (stat_smooth).

Interest on excess reserves

Monetary Base

Currency trend, base

This used to trend along with GDP. It doesn’t anymore.

Money supplies

Basic currency trend (currency component of M1)

datay <- "WCURRNS_YoY"
dtStart = as.Date('1980-01-01')
ylim <- c(0, 17)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

datay <- "WCURRNS_YoY"
dtStart = as.Date('2000-01-01')
ylim <- c(0, 20)
myplot <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)
myplot

The rate of change of money supply could be an indicator of a recession. Let’s see how that compares.

Intervention in the repo market

The federal reserve provides liquidity to the repo market, summary of that action

European central bank

The European central band (ECB) has taken a different path compared to the US Federal Reserve bank.

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Federal Debt

The government is a big driver of the economy, let’s see what it is doing in the debt markets.

datay <- "GFDEBTN"
ylim <- c(0, 28000000)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_Log"
ylim <- c(12, 18)
plotSingleQuick(dfRecession, df.data, datay, ylim)

datay <- "GFDEBTN_YoY"
ylim <- c(-10, 25)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal debt as percent GDP

datay <- "GFDEGDQ188S"
ylim <- c(30, 150)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Federal deficit as percent GDP

datay <- "FYFSGDA188S"
ylim <- c(-30, 5)
plotSingleQuick(dfRecession, df.data, datay, ylim)

Charlie Hatch has a nice format of deficit versus debt:

## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.

Nonfinancial Corporate Business Debt

What about Nonfinancial corporate business and debt securities? Hopefully this doesn’t follow the business loan trends.

That is crazy steep. Time for a log format, see if that brings out the peaks and troughs. That’s a litte better, it looks like there might be a change in slope prior to the recessions.

The derivative doesn’t seem to be much help. There is not much correlation between the zero crossings and the NEBR recessions.

Debt cycle

This analysis roughly follows the ideas in Big Debt Crises book by Ray Dalio.

Total loans

One business cycle theory describes recessions as a market adjustment to mis-allocated assets, often fueled by an credit expansion. That makes the volume of loans an interesting feature to look at. In the presentation of data it looks like the great recession had the largest impact.

Plotting the year over year growth rate helps pull out those small changes in the early years in the data. Peaks can be seen prior to most recessions.

Zoom in to the last couple of decades

As long term interest rates rise, loans should start to tick down. To check this, the total loans and 10 to 1 year spreads are plotted. This is generally the trend observed.

There is a good correlation between these two variables. This next section plots that correction explicitly.

Total loans as percent of GDP

This is the total loans. I think the picture is too broad to point to a specific sector of the economy. The debt burden assumes interest rates are tied to the 10-year treasury: (TOTLNNSA * DGS10) / 100

Commercial and industral loans

Business loans should slow before the recession (a contraction in credit as rates rise).

Commercial and industrial loans as percent of GDP and and income

Look at business debt normalized by GDP over the entire time series. This ratio often peaks at the mid-point of a recession.

https://www.wsj.com/articles/this-isnt-your-fathers-corporate-bond-market-11590574555

“Bonds are behaving more like bank debt, which tends to remain stable or even increase at the onset of recessions, as lenders keep distressed clients afloat—and only later turn off the taps. This was confirmed by a recent report from the Bank for International Settlements. It also found a tight link between this lending cycle and the “real” economy’s booms and busts."

I assume that interest is related to the 10-year treasure: (TOTCINSA * DGS10) / 100

Farm loans

See how the farming sector is fairing.

Real estate loans

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

This gives a big picture, but makes it hard to connect the loans with the income needed to cover those loans. In the next section, loans will be broken up by commercial and residential.

Real Estate (Residential)

In absolute terms the mortgages have increased, but it does not appear to be out of line with the overall economy.

Normalized by GDP it is easier to see the peak in 2008 and that loan levels appear reasonable at the commercial banks.

Maybe the GSE’s are making loans. Take a look at the total mortgages from Z.1 as a percentage of GDP. That does not look too far off trend (ignoring that peak in 2008).

I am assuming that personal income is paying for the mortgages.

Real estate (residential) as percent of GDP and and income

## Warning: Removed 1 rows containing missing values (geom_text).

Consumer loans

Focusing on the consumer sector the growth in debt and incomes can be directly compared. Personal income, as a percent of GDP, remains nearly constant. It is not uncommon for the personal income to rise prior to a recession. Likely this reflect increasing asset prices and market returns. Also interesting to see the loans pick up after interest rates dropped in 1982.

Consumer loans as percent of GDP and and income

Take a closer look since the 2008 recession. Looks like loans are starting to slow as the interest burden rises and incomes remain stable. There are some anomolies in the A065RC1A027NBEA data series because it only updates onces a year. the PI series updates once a month but is noisier and seasonally adjusted. It also shows incomes rising in the middle of the 2008 recession, which doesn’t seem to be accurate.

## Warning: Removed 1 rows containing missing values (geom_text).

## Warning: Removed 1 rows containing missing values (geom_text).

Repo market

This market went through some stress in 2008, it is happening again so setup some plots to watch it.

Nonfincial corporate business security repo asset level

Bonds

T-Bills and Yield Curve

Speaking of loans, interest rates also play into this. This analysis will focus on treasure bills. The 3-month is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

datay <- "TB3MS"
datay.aux <- "DTB3"
ylim <- c(0, 2.5)
dtStart = as.Date('2017-01-01')
p1 <- plotSingle(dfRecession, df.data, "date", datay, getPlotTitle(df.symbols, datay), "Date", 
            getPlotYLabel(df.symbols, datay), c(dtStart, Sys.Date()), ylim, TRUE)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

Check out LIBOR and fed funds rate

The 1-year is plotted below. The yield flattens before a recession as investors go long on bonds and short on equities.

datay <- "DGS10"
datay.aux <- "TNX.Close"
ylim <- c(0, 20)
p1 <- plotSingleQuickModern(datay, ylim)
p1 + geom_line(data=df.data, aes_string(x="date", y=datay.aux, colour=shQuote(datay.aux)), na.rm = TRUE)

Close in, the trend towards inversion be more easily seen. I am also comparing data from the CBOE as well as FRED.

Bond yields are a good proxy for interest rates. As rates rise the theory goes that loans should decrease (inverse correlation).

And a longer window

The yield curve (30 year bond rate minus the 10 year bond rate) may not be a good recession indicator, but a collapse is not good (https://blogs.wsj.com/moneybeat/2018/04/30/theres-more-than-one-part-of-the-yield-curve-getting-flatter/).

The yield curve (10 year bond rate minus the 1 year bond rate) seems to a good indicator of an oncoming recession. It could be a buy indicator by itself.

More recent data

Just the last 24 months or so.

Plot the 10 Year to 3 month over a few decades to see what the outling cases look like

The last two year compare favorably with the period around the 2015-2016 turndown, driven primarily by slowing of the Chinese GDP. Not a debt-driven cycle.

This plot format was suggested by a mises.org article (https://mises.org/wire/yield-curve-accordion-theory), but they only went back to 1988. The date seemed arbitrary so I went back further in time.

Take a look at more recent data

Try looking at a 1-year average of the above time series

High quality bonds

datay <- "AAA"
ylim <- c(2.5, 10)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds to 10-year treasury

High quality bonds long-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('1967-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High quality bonds near-term trend.

datay <- "DGS10ByAAA"
ylim <- c(1, 6.0)
dtStart = as.Date('2007-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

High yield spread

“This data represents the Option-Adjusted Spread (OAS) of the ICE BofAML US Corporate A Index, a subset of the ICE BofAML US Corporate Master Index tracking the performance of US dollar denominated investment grade rated corporate debt publicly issued in the US domestic market. This subset includes all securities with a given investment grade rating A. The ICE BofAML OASs are the calculated spreads between a computed OAS index of all bonds in a given rating category and a spot Treasury curve. An OAS index is constructed using each constituent bond‚Äôs OAS, weighted by market capitalization. When the last calendar day of the month takes place on the weekend, weekend observations will occur as a result of month ending accrued interest adjustments.”

  • ICE Benchmark Administration Limited (IBA), ICE BofAML US Corporate A Option-Adjusted Spread [BAMLC0A3CA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BAMLC0A3CA, July 4, 2019.
datay <- "BAMLC0A3CA"
ylim <- c(0, 7)
dtStart = as.Date('1997-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Municipal bond market

Suggest by a WSJ article, change in volume for high-risk muni’s. Doesn’t look like there is much too it yet.

https://www.wsj.com/articles/risky-municipal-bonds-are-on-a-hot-streak-11558949401?mod=hp_lead_pos3

datay <- "HYMB.Close"
ylim <- c(40, 62)
dtStart = as.Date('2011-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1 <-
  p1 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

datay <- "HYMB.Volume"
ylim <- c(0, 1750000)
p1.vol <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )

p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p1.vol <-
  p1.vol + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


datay <- "GSPC.Open"
datay_aux <- "GSPC.Close"
ylim <- c(1500, d.GSPC.max )
p2 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2015-08-24"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2016-01-08"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-02-05"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )
p2 <-
  p2 + geom_vline(
    xintercept = as.Date("2018-10-11"),
    linetype = "dashed",
    color = "grey",
    size = 1.0
  )


grid.arrange(p1,
             p1.vol,
             p2,
             ncol = 1,
             top = "High Yield Muni's and S&P Price")

Total Loans and yield curve correlation

This relationship was suggest by Charlie and it is an interesting one. As the yield curve flattens (10-year and 1-year rates converge), total loans grow. The generalization is not always accurate, but it does fit.

## `geom_smooth()` using formula 'y ~ x'

I wanted to see how this looked compared to the 3 month

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 282 rows containing non-finite values (stat_smooth).

Consumer loans and yield curve correlation

Compared to business loans, consumer loans seem to have to response to the 10Y to 3M yield curve.

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 311 rows containing non-finite values (stat_smooth).

Business loans and yield curve correlation

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 103 rows containing non-finite values (stat_smooth).

That’s pretty good correlation. Let’s see what the rolling correlation looks like.

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

datay1 <- "TOTLNNSA_YoY"
ylim1 <- c(-10, 20)

datay2 <- "DGS10TO1"
ylim2 <- c(-5, 10)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 720
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

One other items, let’s see how loans do versus the federal funds rate

## `geom_smooth()` using formula 'y ~ x'

EIA Information

Petroleum

Consumption/Sales > Refiner Motor Gasoline Sales Volumes > by Product > Motor Gasoline > by Area > U.S.

Total Energy

Crude Oil and Natural Gas Resource Development > Crude Oil and Natural Gas Drilling Activity Measurements

Baker Hughes Rig Count

BEA Supplemental Estimates, Motor Vehicles

Definitions

Autos–all passenger cars, including station wagons.
Light trucks–trucks up to 14,000 pounds gross vehicle weight, including minivans and
sport utility vehicles. Prior to the 2003 Benchmark Revision light trucks were up to 10,000 pounds.
Heavy trucks–trucks more than 14,000 pounds gross vehicle weight.
Prior to the 2003 Benchmark Revision heavy trucks were more than 10,000 pounds.
Domestic sales–United States (U.S.) sales of vehicles assembled in the U.S., Canada, and Mexico.
Foreign sales–U.S. sales of vehicles produced elsewhere.
Domestic auto production–Autos assembled in the U.S.
Domestic auto inventories–U.S. inventories of vehicles assembled in the U.S., Canada, and Mexico.

TAble 6 - Light Vehicle and Total Vehicle Sales

Auto sales

A WSJ article suggested that auto sales might be a good indicator so bring that to the mix. It does have troughs that correlate with recessions

There might be some seasonal variance in the auto sales so lets take a look at the year over year. The data is pretty noisy, it probably will not make a very good indicator.

BEA Gross Domestic Product

Data in this section come from the Bureau of Economic Analysis.

Table 1.1.5. Gross Domestic Product

[Billions of dollars] Seasonally adjusted at annual rates

A191RC: Gross Domestic Product - Line 1

GDP numbers tend to lag so this series is truly an afterthought. But it does have some correlation with the recessions.

GDP does not reflect the capacity of the economy nor the efficiency. Shrinking capacity and lower prices at constant volumes would indicate improvements in effeciency/productivity which is good for the economy, but does not move the GDP upward.

Looks like the year over year change on the GDP should correlate well with unemployment.

Table 1.1.9. Implicit Price Deflators for Gross Domestic Product

[Index numbers, 2012=100] Seasonally adjusted

A191RD: Gross Domestic Product - Line 1

This is GDP price deflator series.

GDP normalized by CPI

Normalize GDP by CPI

Economic yield curve (GDP to 1-year treasury)

GDP versus the yield on the 1-year. This series was prompted by an article suggesting that the “economic yield curve” should be used to indicate a recession rather than an inverted yield curve. Less of indicator and more of concurrent confirmation of recession. Not sure why they would be related either.

Economic yield curve (GDP to 3-month treasury)

Same idea as above, but applied the 3-month treasury.This one has fewer false triggers, but is not as helpful as 10Y to 3M spread in predicting a recession.

A824RC: National defense Federal Gov’t Expenditures - Line 24

U.S. Bureau of Economic Analysis, Federal Government: National Defense Consumption Expenditures and Gross Investment [FDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FDEFX, April 6, 2021.

A825RC: Nondefense Federal Gov’t Expenditures - Line 25

U.S. Bureau of Economic Analysis, Federal Government: Nondefense Consumption Expenditures and Gross Investment [FNDEFX], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/FNDEFX, April 6, 2021.

Table 6.16D. Corporate Profits by Industry

Select series from Table 6.16D

A051RC: Corporate profits with inventory and capital consumption adjustment

From BEA’s documentation (https://www.bea.gov/media/5671):

“BEA’s featured measure of corporate profits — profits from current production - provides a comprehensive and consistent economic measure of the income earned by all U.S. corporations. As such, it is unaffected by changes in tax laws, and it is adjusted for nonreported and misreported income. It excludes dividend income, capital gains and losses, and other financial flows and adjustments, such as deduction for “bad debt.” Thus, the NIPA measure of profits is a particularly useful analytical measure of the health of the corporate sector. For example, in contrast to other popular measures of corporate profits, the NIPA measure did not show the large run-up in profits during the late 1990s that was primarily attributable to capital gains.

Profits after tax with IVA and CCAdj is equal to corporate profits with IVA and CCAdj less taxes on corporate income. It provides an after-tax measure of profits from current production."

Data is Line 1 of Table 6.16D

A053RC: Corporate profits without inventory and capital consumption adjustment

Profits look a bit flat over the last several years in this series.

Table 2.6. Personal Income and Its Disposition, Monthly

Billions of dollars; months are seasonally adjusted at annual rates.

A065RC Personal Income - Line 1

BEA Account Code: A065RC

Personal income is the income that persons receive in return for their provision of labor, land, and capital used in current production and the net current transfer payments that they receive from business and from government.25 Personal income is equal to national income minus corporate profits with inventory valuation and capital consumption adjustments, taxes on production and imports less subsidies, contributions for government social insurance, net interest and miscellaneous payments on assets, business current transfer payments (net), current surplus of government enterprises, and wage accruals less disbursements, plus personal income receipts on assets and personal current transfer receipts. A Guide to the National Income and Product Accounts of the United States (NIPA) - (http://www.bea.gov/national/pdf/nipaguid.pdf)

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Income [PI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PI, July 11, 2019.

DPCERC: Personal consumption expenditures (PCE) - Table 2.1, Line 29

BEA Account Code: DPCERC Personal consumption expenditures (PCE) is the primary measure of consumer spending on goods and services in the U.S. economy. 1 It accounts for about two-thirds of domestic final spending, and thus it is the primary engine that drives future economic growth. PCE shows how much of the income earned by households is being spent on current consumption as opposed to how much is being saved for future consumption. -https://www.bea.gov/system/files/2019-12/Chapter-5.pdf

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures [PCE], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCE, June 12, 2020

DPCERG: Personal consumption expenditures Price Index (PCEPI) - Table 2.1, Line 29

BEA Account Code: DPCERG The gross domestic product price index measures changes in prices paid for goods and services produced in the United States, including those exported to other countries. Prices of imports are excluded. The gross domestic product implicit price deflator, or GDP deflator, basically measures the same things and closely mirrors the GDP price index, although the two price measures are calculated differently. The GDP deflator is used by some firms to adjust payments in contracts.

The gross domestic purchases price index is BEA’s featured measure of inflation for the U.S. economy overall. It measures changes in prices paid by consumers, businesses, and governments in the United States, including the prices of the imports they buy.

BEA’s closely followed personal consumption expenditures price index, or PCE price index, is a narrower measure. It looks at the changing prices of goods and services purchased by consumers in the United States. It’s similar to the Bureau of Labor Statistics’ consumer price index for urban consumers. The two indexes, which have their own purposes and uses, are constructed differently, resulting in different inflation rates.

The PCE price index is known for capturing inflation (or deflation) across a wide range of consumer expenses and for reflecting changes in consumer behavior. For example, if the price of beef rises, shoppers may buy less beef and more chicken. Also, BEA revises previously published PCE data to reflect updated information or new methodology, providing consistency across decades of data that’s valuable for researchers. The PCE price index is used primarily for macroeconomic analysis and forecasting. -https://www.bea.gov/resources/learning-center/what-to-know-prices-inflation

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Consumption Expenditures: Chain-type Price Index [PCEPI], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PCEPI, April 25, 2021.

A072RC: Personal Savings Rate - Line 35

Consumers tend to pull down their savings rates as unemployment decreases and market conditions improve. This series has tended to be unreliable due to the size of revisions during the comprehensive update carried out by the BEA. The last update on this series moved the rate from 4.2 to 6.7 percent.

(https://www.bloomberg.com/news/articles/2018-07-27/americans-have-been-saving-much-more-than-thought-new-data-show)

BEA Account Code: A072RC Personal saving as a percentage of disposable personal income (DPI), frequently referred to as “the personal saving rate,” is calculated as the ratio of personal saving to DPI. Personal saving is equal to personal income less personal outlays and personal taxes; it may generally be viewed as the portion of personal income that is used either to provide funds to capital markets or to invest in real assets such as residences.(https://www.bea.gov/national/pdf/all-chapters.pdf) A Guide to the National Income and Product Accounts of the United States (NIPA).

Suggested Citation: U.S. Bureau of Economic Analysis, Personal Saving Rate [PSAVERT], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/PSAVERT, July 9, 2019.

Take a closer look at the last decade

The relationship between personal savings and unemployment (U-3) can be better visualized with a scatter plot

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 189 rows containing non-finite values (stat_smooth).

The fit does not explain most of what is in the plot. Lets take a look at the rolling correlation.

datay1 <- "UNRATE"
ylim1 <- c(2, 12)

datay2 <- "PSAVERT"
ylim2 <- c(0, 35)

dtStart <- as.Date("1jan1985","%d%b%Y")

w <- 360
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Personal savings to household net worth

A relationship between personal savings and household networth can be seen in a scatter plot. This was suggested by a WSJ article (https://blogs.wsj.com/dailyshot/2018/02/23/the-daily-shot-reasons-for-declining-u-s-household-savings-rate/).

## `geom_smooth()` using formula 'y ~ x'
## Warning: Removed 437 rows containing non-finite values (stat_smooth).

U.S. Census Bureau

U.S. International Trade in Goods and Services (FT900)

U.S. Bureau of Economic Analysis and U.S. Census Bureau, U.S. Imports of Goods by Customs Basis from China [IMPCH], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/IMPCH, October 5, 2019.

New Houses Sold and For Sale by Stage of Construction and Median Number of Months on Sales Market

Read an article suggesting that housing sales and sales growth could be useful. FRED only has new home data so start there.

datay <- "HSN1FNSA"
ylim <- c(0, 200)
dtStart = as.Date('1964-01-01')
p1 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA"
ylim <- c(0, 600)
p2 <- plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "HNFSUSNSA.minus.HSN1FNSA"
ylim <- c(0, 600)
p3 <-
  plotSingle(
    dfRecession,
    df.data,
    "date",
    datay,
    getPlotTitle(df.symbols, datay),
    "Date",
    getPlotYLabel(df.symbols, datay),
    c(dtStart, Sys.Date()),
    ylim,
    TRUE
  )

grid.arrange(p1,
             p2,
             p3,
             ncol = 1,
             top = "New Housing Sales")

New housing yoy

New Privately-Owned Housing Units Authorized in Permit-Issuing Places

As provided by the Census, start occurs when excavation begins for the footings or foundation of a building. All housing units in a multifamily building are defined as being started when this excavation begins. Beginning with data for September 1992, estimates of housing starts include units in structures being totally rebuilt on an existing foundation.

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Housing Starts: Total: New Privately Owned Housing Units Started [HOUST], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/HOUST, June 13, 2020.

Take a look at privately owned starts

New Privately-Owned Houses Sold and For Sale

Suggested Citation: U.S. Census Bureau and U.S. Department of Housing and Urban Development, Median Sales Price of Houses Sold for the United States [MSPUS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/MSPUS, June 13, 2020.

Finally, take a look at starts times the median price

Durable Goods

Suggested Citation: U.S. Census Bureau, Manufacturers’ New Orders: Durable Goods [UMDMNO], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/UMDMNO, April 26, 2021.

Durable goods, not seasonally adjusted, divided by GDP

Durable goods, seasonally adjusted, divided by GDP

Federal reserve board H.8: Assets and Liabilities of Commercial Banks in the United States

Page 4: Not Seasonally adjusted, billions of dollars

Commercial and industrial loans, all commercial banks - Line 10

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Commercial and Industrial Loans, All Commercial Banks [BUSLOANS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/BUSLOANS, July 11, 2019.

Taking a look at the difference in SA and NSA series. Seasonal adjustments do vary, but do not seem to be related to recessions.

The raw series is just too steep for any kind of machine learnine. This needs to be converted to log scale.

That’s a little better, let’s see what the smoothed derivative looks like.

That is odd…looks like this doesn’t cross zero unless we are getting close to, or into, a recession. The year over year tells about the same story. Might be a good indication of the end of a recession.

Consumer loans, all commercial banks - Line 20

Suggested Citation: Board of Governors of the Federal Reserve System (US), Consumer Loans, All Commercial Banks [CONSUMERNSA], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/CONSUMERNSA, July 11, 2019.

That spike in consumer loans is due to

“April 9, 2010 (Last revised September 23, 2011): As of the week ending March 31, 2010, domestically chartered banks and foreign-related institutions had consolidated onto their balance sheets the following assets and liabilities of off-balance-sheet vehicles, owing to the adoption of FASB’s Financial Accounting Statements No. 166 (FAS 166),”Accounting for Transfers of Financial Assets," and No. 167 (FAS 167), “Amendments to FASB Interpretation No. 46(R).”

This included a consumer loans, credit cards and other revolving plans change of $321.9B. That was a lot of off-balance-sheet bank assets.

Deposits, All Commercial Banks, all commercial banks - Line 34

Data taken from H.8 Assets and Liabilities of Commercial Banks in the United States. Take a look at SA and NSA data series as weekly and month updates. It should all be similar at this scale.

Suggested Citation: Board of Governors of the Federal Reserve System (US), Deposits, All Commercial Banks [DPSACBW027SBOG], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/DPSACBW027SBOG, May 14, 2020.

Federal reserve board Z.1: Financial Accounts of the United States

From the FRED website (https://fred.stlouisfed.org/release?rid=52):

"The Financial Accounts (formerly known as the Flow of Funds accounts) are a set of financial accounts used to track the sources and uses of funds by sector. They are a component of a system of macroeconomic accounts including the National Income and Product accounts (NIPA) and balance of payments accounts, all of which serve as a comprehensive set of information on the economy’s performance.(1) Some important inferences that can be drawn from the Financial accounts are the financial strength of a given sector, new economic trends, changes in the composition of wealth, and development of new financial instruments over time.(1)

Sectors are compiled into three categories: households, nonfinancial businesses, and banks. The sources of funds for a sector are its internal funds (savings from income after consumption) and external funds (loans from banks and other financial intermediaries). (1) Funds for a given sector are used for its investments in physical and financial assets. Dividing sources and uses of funds into two categories helps the staff of the Federal Reserve System pay particular attention to external sources of funds and financial uses of funds.(2) One example is whether households are borrowing more from banks—or in other words, whether household debt is rising. Another example might be whether banks are using more of their funds to provide loans to consumers. Transactions within a sector are not shown in the accounts; however, transactions between sectors are.(2) Monitoring the external flows of funds provides insights into a sector’s health and the performance of the economy as a whole.

Data for the Financial accounts are compiled from a large number of reports and publications, including regulatory reports such as those submitted by banks, tax filings, and surveys conducted by the Federal Reserve System.(2) The Financial accounts are published quarterly as a set of tables in the Federal Reserve’s Z.1 statistical release.

  1. Teplin, Albert M. “The U.S. Flow of Funds Accounts and Their Uses.” Federal Reserve Bulletin, July 2001; http://www.federalreserve.gov/pubs/bulletin/2001/0701lead.pdf.
  2. Board of Governors of the Federal Reserve System. “Guide to the Flow of Funds Accounts.” 2000, http://www.federalreserve.gov/apps/fof/."

L.102 Nonfinancial Business

FL102051003.Q: Nonfinancial corporate business; security repurchase agreements; asset

Asset level of nonfinancial business security repo agreements. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL102051003&t=

L.214 Loans

FL894123005.Q: All sectors; total loans; liability

Sum of domestic financial sectors, all sectors, total mortgages, and households/non-profits. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL894123005&t=L.107&bc=L.107:FL793068005&suf=Q

FL793068005.Q: Domestic financial sectors; depository institution loans n.e.c.; asset

Sum of Monetary authority; depository institution loans n.e.c.; asset and Private depository institutions; depository institution loans n.e.c.; asset. federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL793068005&t=L.214&suf=Q

FL893169005.Q: All sectors; other loans and advances; liability

Sum of finance, government, and chartered institutions asset levels. https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893169005&t=L.214&suf=Q

FL893065105.Q: All sectors; home mortgages; asset

https://www.federalreserve.gov/apps/fof/DisplayTable.aspx?t=L.214

FL893065405.Q: All sectors; multifamily residential mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065405&t=L.214&suf=Q

FL893065505.Q: All sectors; commercial mortgages; asset

https://www.federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL893065505&t=L.214&suf=Q

FL153166000.Q: Households and nonprofit organizations; consumer credit; liability

federalreserve.gov/apps/fof/SeriesAnalyzer.aspx?s=FL153166000&t=L.214&suf=Q

B.101 Balance Sheet of Households and Nonprofit Organizations

FL152000005.Q: Households and nonprofit organizations; total assets, Level

string.source ID: FL152000005.Q.

FL152090006.Q: Household Net Worth as Percentage of Disposable Personal Income

string.source ID: FL152090006.Q. Household networth tends to fall as a recession start.

Productivity Yield Curve

GDP versus productivity

Manufacturing output and employees

Not sure if these relates to a recession, but fascinating to see how output and employees change with time.

datay <- "OUTMS"
ylim <- c(60, 120)
dtStart = as.Date('1987-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "MANEMP"
ylim <- c(10000, 20000)
dtStart = as.Date('1948-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "PRS30006163"
ylim <- c(40, 120)
dtStart = as.Date('1986-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Shipping volumes might be helpful in determining state of the economy.

datay <- "FRGSHPUSM649NCIS"
ylim <- c(0.8, 1.4)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

datay <- "FRGSHPUSM649NCIS_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Freight, loosely, moves inversely to the trade deficit.

datay <- "BOPGTB_YoY"
ylim <- c(-30, 30)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

World bank air transportation. Only updated annually so less usefull, but interesting reference to above.

datay <- "WWDIWLDISAIRGOODMTK1"
ylim <- c(0, 250000)
dtStart = as.Date('1999-01-01')
plotSingleQuick(dfRecession, df.data, datay, ylim, dtStart)

Gross private domestic investment

Spending most certainly tips down prior to a recession. The gross private domestic investment data series, plotted in log format below, show how private investment pulls back prior to recessions.

The change in direction is a little easier to see if the derivative is plotted, first YoY then the smoothed derivative

Velocity

Productivity

Date range to match census data

PMI

Industrial Production

This is a look at manufacturing industrial production. The yoY change should be a leading indicator of unemployment.

Housing

Take a look at housing starts. These can drop as rates rise.

Case-schiller price index

Population data

Many of the economic series can be better understood if normalized by population. Basic population and worker data from FRED.

Population to GDP

Look at GDP divided by CPI per person. It flattens and even dips a little prior to a recession. Might be worth looking at the derivative of this series.

That is worth a closer look

datay1 <- "GDPBYCPIAUCSLBYPOPTHM_SmoothDer"
ylim1 <- c(-5, 5)

datay2 <- "RecInit_Smooth"
ylim2 <- c(0, 1)

dtStart <- as.Date("1jan1960","%d%b%Y")

w <- 30
corrName <- calcRollingCorr(dfRecession, df.data, df.symbols, datay1, ylim1, datay2, ylim2, w, dtStart)

Correlation Study

Detailed correlations are explored above. Before concluding, let’s take a look at some overall correlation values to see if anything pops out.

Commodities

As mentioned above, copper, year over year, has some correlation with the recession initiation. It could be useful.

GDP Series

GDP, normalized first by CPI and then by population, looks like it migh correlate inversely with the recession indicators

Financials

Let’s see where we are so far. The correlation plot confirms some of the speculation above. The S&P 500 (GSPC.Open) is well correlated with industrial production (INDPRO), business loans (BUSLOANS), total loans (TOTLNNSA) , and nonfinancial corporate business debt (NCBDBIQ027S).

In this case, I want and indicator that rises prior to a recession. It looks like the unemployment rate (UNRATE), real personal income (W875RX1), and the yield curve (DGS10TO1) are all inversely correlated with the recession initiation indicator.

I thought the modified recession initiation would be a harder match, but there are quite a few correlated variables. Lets take a look at some of those in more detail

Complete list of symbols

Since it is tedious to do this one at a time, all the symbols were entered into a data frame, loaded, and aggregated together in a single xts object.

This is the complete list of symbol names and sources used in the project.